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Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h Investment Strategy (Quantitative Trading) | 🛑 | Watch "LIVE" and 'COPY' this strategy in real time: 🔗 Link: www.tradingview.com Hello, welcome, feel free 🌹💐 Since the stone age to the most technological age, one thing has not changed, that which continues impress human beings the most, is the other human being! Deep down, it's all very simple or very complicated, depends on how you look at it. I believe that everyone was born to do something very well in life. But few are those who have, let's use the word 'luck' . Few are those who have the 'luck' to discover this thing. That is why few are happy and successful in their jobs and professions. Thank God I had this 'luck' , and discovered what I was born to do well. And I was born to program. 👨‍💻 📋 Summary : Project Titan 0️⃣ : 🦄 Project Titan 1️⃣ : ⚖️ Quantitative THEMIS 2️⃣ : 🏛️ Titan Community 3️⃣ : 👨‍💻 Who am I ❔ 4️⃣ : ❓ What is Statistical/Probabilistic Trading ❓ 5️⃣ : ❓ How Statistical/Probabilistic Trading works ❓ 6️⃣ : ❓ Why use a Statistical/Probabilistic system ❓ 7️⃣ : ❓ Why the human brain is not prepared to do Trading ❓ 8️⃣ : ❓ What is Backtest ❓ 9️⃣ : ❓ How to build a Consistent system ❓ 🔟 : ❓ What is a Quantitative Trading system ❓ 1️⃣1️⃣ : ❓ How to build a Quantitative Trading system ❓ 1️⃣2️⃣ : ❓ How to Exploit Market Anomalies ❓ 1️⃣3️⃣ : ❓ What Defines a Robust, Profitable and Consistent System ❓ 1️⃣4️⃣ : 🔧 Fixed Technical 1️⃣5️⃣ : ❌ Fixed Outputs : 🎯 TP(%) & 🛑SL(%) 1️⃣6️⃣ : ⚠️ Risk Profile 1️⃣7️⃣ : ⭕ Moving Exits : (Indicators) 1️⃣8️⃣ : 💸 Initial Capital 1️⃣9️⃣ : ⚙️ Entry Options 2️⃣0️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Third-Party Services' 2️⃣1️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Exchanges 2️⃣2️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Messaging Services' 2️⃣3️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : '🧲🤖Copy-Trading' 2️⃣4️⃣ : ❔ Why be a Titan Pro 👽❔ 2️⃣5️⃣ : ❔ Why be a Titan Aff 🛸❔ 2️⃣6️⃣ : 📋 Summary : ⚖️ Strategy: Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h 2️⃣7️⃣ : 📊 PERFORMANCE : 🆑 Conservative 2️⃣8️⃣ : 📊 PERFORMANCE : Ⓜ️ Moderate 2️⃣9️⃣ : 📊 PERFORMANCE : 🅰 Aggressive 3️⃣0️⃣ : 🛠️ Roadmap 3️⃣1️⃣ : 🧻 Notes ❕ 3️⃣2️⃣ : 🚨 Disclaimer ❕❗ 3️⃣3️⃣ : ♻️ ® No Repaint 3️⃣4️⃣ : 🔒 Copyright ©️ 3️⃣5️⃣ : 👏 Acknowledgments 3️⃣6️⃣ : 👮 House Rules : 📺 TradingView 3️⃣7️⃣ : 🏛️ Become a Titan Pro member 👽 3️⃣8️⃣ : 🏛️ Be a member Titan Aff 🛸 0️⃣ : 🦄 Project Titan This is the first real, 100% automated Quantitative Strategy made available to the public and the pinescript community for TradingView. You will be able to automate all signals of this strategy for your broker , centralized or decentralized and also for messaging services : Discord, Telegram or Twitter . This is the first strategy of a larger project, in 2023, I will provide a total of 6 100% automated 'Quantitative' strategies to the pinescript community for TradingView. The future strategies to be shared here will also be unique , never before seen, real 'Quantitative' bots with real, validated results in real operation. Just like the 'Quantitative THEMIS' strategy, it will be something out of the loop throughout the pinescript/tradingview community, truly unique tools for building mutual wealth consistently and continuously for our community. 1️⃣ : ⚖️ Quantitative THEMIS : Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h This is a truly unique and out of the curve strategy for BTC /USD . A truly real strategy, with real, validated results and in real operation. A unique tool for building mutual wealth, consistently and continuously for the members of the Titan community. Initially we will operate on a monthly, quarterly, annual or biennial subscription service. Our goal here is to build a great community, in exchange for an extremely fair value for the use of our truly unique tools, which bring and will bring real results to our community members. With this business model it will be possible to provide all Titan users and community members with the purest and highest degree of sophistication in the market with pinescript for tradingview, providing unique and truly profitable strategies. My goal here is to offer the best to our members! The best 'pinescript' tradingview service in the world! We are the only Start-Up in the world that will decentralize real and full access to truly real 'quantitative' tools that bring and will bring real results for mutual and ongoing wealth building for our community. 2️⃣ : 🏛️ Titan Community : 👽 Pro 🔁 Aff 🛸 Become a Titan Pro 👽 To get access to the strategy: "Quantitative THEMIS" , and future Titan strategies in a 100% automated way, along with all tutorials for automation. Pro Plans: 30 Days, 90 Days, 12 Months, 24 Months. 👽 Pro 🅼 Monthly 👽 Pro 🆀 Quarterly 👽 Pro🅰 Annual 👽 Pro👾Two Years You will have access to a truly unique system that is out of the curve . A 100% real, 100% automated, tested, validated, profitable, and in real operation strategy. Become a Titan Affiliate 🛸 By becoming a Titan Affiliate 🛸, you will automatically receive 50% of the value of each new subscription you refer . You will receive 50% for any of the above plans that you refer . This way we will encourage our community to grow in a fair and healthy way, because we know what we have in our hands and what we deliver real value to our users. We are at the highest level of sophistication in the market, the consistency here and the results here speak for themselves. So growing our community means growing mutual wealth and raising collective conscience. Wealth must be created not divided. And here we are creating mutual wealth on all ends and in all ways. A non-zero sum system, where everybody wins. 3️⃣ : 👨‍💻 Who am I ❔ My name is FilipeSoh I am 26 years old, Technical Analyst, Trader, Computer Engineer, pinescript Specialist, with extensive experience in several languages and technologies. For the last 4 years I have been focusing on developing, editing and creating pinescript indicators and strategies for Tradingview for people and myself. Full-time passionate workaholic pinescript developer with over 10,000 hours of pinescript development. • Pinescript expert ▬Tradingview. • Specialist in Automated Trading • Specialist in Quantitative Trading. • Statistical/Probabilistic Trading Specialist - Mark Douglas Scholl. • Inventor of the 'Classic Forecast' Indicators. • Inventor of the 'Backtest Table'. 4️⃣ : ❓ What is Statistical/Probabilistic Trading ❓ Statistical/probabilistic trading is the only way to get a positive mathematical expectation regarding the market and consequently that is the only way to make money consistently from it. I will present below some more details about the Quantitative THEMIS strategy, it is a real strategy, tested, validated and in real operation, 'Skin in the Game' , a consistent way to make money with statistical/probabilistic trading in a 100% automated. I am a Technical Analyst , I used to be a Discretionary Trader , today I am 100% a Statistical Trader . I've gotten rich and made a lot of money, and I've also lost a lot with 'leverage'. That was a few years ago. The book that changed everything for me was "Trading in The Zone" by Mark Douglas. That's when I understood that the market is just a game of statistics and probability, like a casino! It was then that I understood that the human brain is not prepared for trading, because it involves triggers and mental emotions. And emotions in trading and in making trading decisions do not go well together, not in the long run, because you always have the burden of being wrong with the outcome of that particular position. But remembering that the market is just a statistical game! 5️⃣ : ❓ How Statistical/Probabilistic Trading works ❓ Let's use a 'coin' as an example: If we toss a 'coin' up 10 times. Do you agree that it is impossible for us to know exactly the result of the 'plays' before they actually happen? As in the example above, would you agree, that we cannot "guess" the outcome of a position before it actually happens? As much as we cannot "guess" whether the coin will drop heads or tails on each flip. We can analyze the "backtest" of the 10 moves made with that coin: If we analyze the 10 moves and count the number of times the coin fell heads or tails in a specific sequence, we then have a percentage of times the coin fell heads or tails, so we have a 'backtest' of those moves. Then on the next flip we can now assume a point or a favorable position for one side, the side with the highest probability . In a nutshell, this is more or less how probabilistic statistical trading works. As Statistical Traders we can never say whether such a Trader/Position we take will be a winner or a loser. But still we can have a positive and consistent result in a "sequence" of trades, because before we even open a position, backtests have already been performed so we identify an anomaly and build a system that will have a positive statistical advantage in our favor over the market. The advantage will not be in one trade itself, but in the "sequence" of trades as a whole! Because our system will work like a casino, having a positive mathematical expectation relative to the players/market. Design, develop, test models and systems that can take advantage of market anomalies, until they change. Be the casino! - Mark Douglas 6️⃣ : ❓ Why use a Statistical/Probabilistic system ❓ In recent years I have focused and specialized in developing 100% automated trading systems, essentially for the cryptocurrency market. I have developed many extremely robust and efficient systems, with positive mathematical expectation towards the market. These are not complex systems per se , because here we want to avoid 'over-optimization' as much as possible. As Da Vinci said: "Simplicity is the highest degree of sophistication". I say this because I have tested, tried and developed hundreds of systems/strategies. I believe I have programmed more than 10,000 unique indicators/strategies, because this is my passion and purpose in life. I am passionate about what I do, completely! I love statistical trading because it is the only way to get consistency in the long run! This is why I have studied, applied, developed, and specialized in 100% automated cryptocurrency trading systems. The reason why our systems are extremely "simple" is because, as I mentioned before, in statistical trading we want to exploit the market anomaly to the maximum, that is, this anomaly will change from time to time, usually we can exploit a trading system efficiently for about 6 to 12 months, or for a few years, that is; for fixed 'scalpers' systems. Because at some point these anomalies will be identified , and from the moment they are identified they will be exploited and will stop being anomalies . With the system presented here; you can even copy the indicators and input values shared here; However; what I have to offer you is: it is me , our team , and our community ! That is, we will constantly monitor this system, for life , because our goal here is to create a unique , perpetual , profitable , and consistent system for our community. Myself , our team and our community will keep this script periodically updated , to ensure the positive mathematical expectation of it. So we don't mind sharing the current parameters and values , because the real value is also in the future updates that this system will receive from me and our team , guided by our culture and our community of real users ! As we are hosted on 'tradingview', all future updates for this strategy, will be implemented and updated automatically on your tradingview account. What we want here is: to make sure you get gains from our system, because if you get gains , our ecosystem will grow as a whole in a healthy and scalable way, so we will be generating continuous mutual wealth and raising the collective consciousness . People Need People: 3️⃣🅿 7️⃣ : ❓ Why the human brain is not prepared to do Trading ❓ Today my greatest skill is to develop statistically profitable and 100% automated strategies for 'pinescript' tradingview. Note that I said: 'profitable' because in fact statistical trading is the only way to make money in a 'consistent' way from the market. And consequently have a positive wealth curve every cycle, because we will be based on mathematics, not on feelings and news. Because the human brain is not prepared to do trading. Because trading is connected to the decision making of the cerebral cortex. And the decision making is automatically linked to emotions, and emotions don't match with trading decision making, because in those moments, we can feel the best and also the worst sensations and emotions, and this certainly affects us and makes us commit grotesque mistakes! That's why the human brain is not prepared to do trading. If you want to participate in a fully automated, profitable and consistent trading system; be a Titan Pro 👽 I believe we are walking an extremely enriching path here, not only in terms of financial returns for our community, but also in terms of knowledge about probabilistic and automated statistical trading. You will have access to an extremely robust system, which was built upon very strong concepts and foundations, and upon the world's main asset in a few years: Bitcoin . We are the tip of the best that exists in the cryptocurrency market when it comes to probabilistic and automated statistical trading. Result is result! Me being dressed or naked. This is just the beginning! But there is a way to consistently make money from the market. Being the Casino! - Mark Douglas 8️⃣ : ❓ What is Backtest ❓ Imagine the market as a purely random system, but even in 'randomness' there are patterns. So now imagine the market and statistical trading as follows: Repeating the above 'coin' example, let's think of it as follows: If we toss a coin up 10 times again. It is impossible to know which flips will have heads or tails, correct? But if we analyze these 10 tosses, then we will have a mathematical statistic of the past result, for example, 70 % of the tosses fell 'heads'. That is: 7 moves fell on "heads" . 3 moves fell on "tails" . So based on these conditions and on the generic backtest presented here, we could adopt " heads " as our system of moves, to have a statistical and probabilistic advantage in relation to the next move to be performed. That is, if you define a system, based on backtests , that has a robust positive mathematical expectation in relation to the market you will have a profitable system. For every move you make you will have a positive statistical advantage in your favor over the market before you even make the move. Like a casino in relation to all its players! The casino does not have an advantage over one specific player, but over all players, because it has a positive mathematical expectation about all the moves that night. The casino will always have a positive statistical advantage over its players. Note that there will always be real players who will make real, million-dollar bankrolls that night, but this condition is already built into the casino's 'strategy', which has a pre-determined positive statistical advantage of that night as a whole. Statistical trading is the same thing, as long as you don't understand this you will keep losing money and consistently. 9️⃣ : ❓ How to build a Consistent system ❓ See most traders around the world perform trades believing that that specific position taken will make them filthy rich, because they simply believe faithfully that the position taken will be an undoubted winner, based on a trader's methodology: 'trading a trade' without analyzing the whole context, just using 'empirical' aspects in their system. But if you think of trading, as a sequence of moves. You see, 'a sequence' ! When we think statistically, it doesn't matter your result for this , or for the next specific trade , but the final sequence of trades as a whole. As the market has a random system of results distribution , if your system has a positive statistical advantage in relation to the market, at the end of that sequence you'll have the biggest probability of having a winning bank. That's how you do real trading! And with consistency! Trading is a long term game, but when you change the key you realize that it is a simple game to make money in a consistent way from the market, all you need is patience. Even more when we are based on Bitcoin, which has its 'Halving' effect where, in theory, we will never lose money in 3 to 4 years intervals, due to its scarcity and the fact that Bitcoin is the 'discovery of digital scarcity' which makes it the digital gold, we believe in this thesis and we follow Satoshi's legacy. So align Bitcoin with a probabilistic statistical trading system with a positive mathematical expectation of the market and 100% automated with the long term, and all you need is patience, and you will become rich. In fact Bitcoin by itself is already a path, buy, wait for each halving and your wealth will be maintained. No inflation, unlike fiat currencies. This is a complete and extremely robust strategy, with the most current possible and 'not possible' techniques involved and applied here. Today I am at another level in developing 100% automated 'quantitative' strategies. I was born for this! 🔟 : ❓ What is a Quantitative Trading system ❓ In addition to having access to a revolutionary strategy you will have access to disruptive 100% multifunctional tables with the ability to perform 'backtests' for better tracking and monitoring of your system on a customized basis. I would like to emphasize one thing, and that is that you keep this in mind. Today my greatest skill in 'pinescript' is to build indicators, but mainly strategies, based on statistical and probabilistic trading, with a postive mathematical expectation in relation to the market, in a 100% automated way. This with the goal of building a consistent and continuous positive equity curve through mathematics using data, converting it into statistical / probabilistic parameters and applying them to a Quantitative model. Before becoming a Quantitative Trader , I was a Technical Analyst and a Discretionary Trader . First as a position trader and then as a day trader. Before becoming a Trader, I trained myself as a Technical Analyst , to masterly understand the shape and workings of the market in theory. But everything changed when I met 'Mark Douglas' , when I got to know his works, that's when my head exploded 🤯, and I started to understand the market for good! The market is nothing more than a 'random' system of distributing results. See that I said: 'random' . Do yourself a mental exercise. Is there really such a thing as random ? I believe not, as far as we know maybe the 'singularity'. So thinking this way, to translate, the market is nothing more than a game of probability, statistics and pure mathematics. Like a casino! What happens is that most traders, whenever they take a position, take it with all the empirical certainty that such position will win or lose, and do not take into consideration the total sequence of results to understand their place in the market. Understanding your place in the market gives you the ability to create and design systems that can exploit the present market anomaly, and thus make money statistically, consistently, and 100% automated. Thinking of it this way, it is easy to make money from the market. There are many ways to make money from the market, but the only consistent way I know of is through 'probabilistic and automated statistical trading'. 1️⃣1️⃣ : ❓ How to build a Quantitative Trading system ❓ There are some fundamental points that must be addressed here in order to understand what makes up a system based on statistics and probability applied to a quantitative model. When we talk about 'discretionary' trading, it is a trading system based on human decisions after the defined 'empirical' conditions are met. It is quite another thing to build a fully automated system without any human interference/interaction . That said: Building a statistically profitable system is perfectly possible, but this is a high level task , but with possible high rewards and consistent gains. Here you will find a real "Skin In The Game" strategy. With all due respect, but the vast majority of traders who post strategies on TradingView do not understand what they are doing. Most of them do not understand the minimum complexity involved in the main variable for the construction of a real strategy, the mother variable: "strategy". I say this by my own experience, because I have analyzed practically all the existing publications of TradingView + 200,000 indicators and strategies. I breathe pinescript, I eat pinescript, I sleep pinescript, I bathe pinescript, I live TradingView. But the main advantage for the TradingView users, is that all entry and exit orders made by this strategy can be checked and analyzed thoroughly, to validate and prove the veracity of this strategy, because this is a 100% real strategy. Here there is a huge world of possibilities, but only one way to build a 'pinescript strategy' that will work correctly aligned to the real world with real results . There are some fundamental points to take into consideration when building a profitable trading system: The most important of these for me is: 'DrawDown' . Followed by: 'Hit Rate' . And only after that we use the parameter: 'Profit'. See, this is because here, we are dealing with the 'imponderable' , and anything can happen in this scenario. But there is one thing that makes us sleep peacefully at night, and that is: controlling losses . That is, in other words: controlling the DrawDown . The amateur is concerned with 'winning', the professional is concerned with conserving capital. If we have the losses under control, then we can move on to the other two parameters: hit rate and profit. See, the second most important factor in building a system is the hit rate. I say this from my own experience. I have worked with many systems with a 'low hit rate', but extremely profitable. For example: systems with hit rates of 40 to 50%. But as much as statistically and mathematically the profit is rewarding, operating systems with a low hit rate is always very stressful psychologically. That's why there are two big reasons why when I build an automated trading system, I focus on the high hit rate of the system, they are 1 - To reduce psychological damage as much as possible . 2 - And more important , when we create a system with a 'high hit rate' , there is a huge intrinsic advantage here, that most statistic traders don't take in consideration. That is: knowing more quickly when the system stops being functional. The main advantage of a system with a high hit rate is: to identify when the system stops being functional and stop exploiting the market's anomaly. Look: When we are talking about trading and random distribution of results on the market, do you agree that when we create a trading system, we are focused on exploring some anomaly of that market? When that anomaly is verified by the market, it will stop being functional with time. That's why trading systems, 'scalpers', especially for cryptocurrencies, need constant monitoring, quarterly, semi-annually or annually. Because market movements change from time to time. Because we go through different cycles from time to time, such as congestion cycles, accumulation , distribution , volatility , uptrends and downtrends . 1️⃣2️⃣ : ❓ How to Exploit Market Anomalies ❓ You see there is a very important point that must be stressed here. As we are always trying to exploit an 'anomaly' in the market. So the 'number' of indicators/tools that will integrate the system is of paramount importance. But most traders do not take this into consideration. To build a professional, robust, consistent, and profitable system, you don't need to use hundreds of indicators to build your setup. This will actually make it harder to read when the setup stops working and needs some adjustment. So focusing on a high hit rate is very important here, this is a fundamental principle that is widely ignored , and with a high hit rate, we can know much more accurately when the system is no longer functional much faster. As Darwin said: "It is not the strongest or the most intelligent that wins the game of life, it is the most adapted. So simple systems, as contradictory as it may seem, are more efficient, because they help to identify inflection points in the market much more quickly. 1️⃣3️⃣ : ❓ What Defines a Robust, Profitable and Consistent System ❓ See I have built, hundreds of thousands of indicators and 'pinescript' strategies, hundreds of thousands. This is an extremely professional, robust and profitable system. Based on the currency pairs: BTC /USDT There are many ways and avenues to build a profitable trading setup/system. And actually this is not a difficult task, taking in consideration, as the main factor here, that our trading and investment plan is for the long term, so consequently we will face scenarios with less noise. He who is in a hurry eats raw. As mentioned before. Defining trends in pinescript is technically a simple task, the hardest task is to determine congestion zones with low volume and volatility, it's in these moments that many false signals are generated, and consequently is where most setups face their maximum DrawDown. That's why this strategy was strictly and thoroughly planned, built on a very solid foundation, to avoid as much noise as possible, for a positive and consistent equity curve in each market cycle, 'Consistency' is our 'Mantra' around here. 1️⃣4️⃣ : 🔧 Fixed Technical • Strategy: Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h • Pair: BTC/USDTP • Time Frame: 4 hours • Broker: Binance (Recommended) For a more conservative scenario, we have built the Quantitative THEMIS for the 4h time frame, with the main focus on consistency. So we can avoid noise as much as possible! 1️⃣5️⃣ : ❌ Fixed Outputs : 🎯 TP(%) & 🛑SL(%) In order to build a 'perpetual' system specific to BTC/USDT, it took a lot of testing, and more testing, and a lot of investment and research. There is one initial and fundamental point that we can address to justify the incredible consistency presented here. That fundamental point is our exit via Take Profit or Stop Loss percentage (%). 🎯 Take Profit (%) 🛑 Stop Loss (%) See, today I have been testing some more advanced backtesting models for some cryptocurrency systems. In which I perform 'backtest of backtest', i.e. we use a set of strategies each focused on a principle, operating individually, but they are part of something unique, i.e. we do 'backtests' of 'backtests' together. What I mean is that we do a lot of backtesting around here. I can assure you, that always the best output for a trading system is to set fixed output values! In other words: 🎯 Take Profit (%) 🛑 Stop Loss (%) This happens because statistically setting fixed exit structures in the vast majority of times, presents a superior result on the capital/equity curve, throughout history and for the vast majority of setups compared to other exit methods. This is due to a mathematical principle of simplicity, 'avoiding more noise'. Thus whenever the Quantitative THEMIS strategy takes a position it has a target and a defined maximum stop percentage. 1️⃣6️⃣ : ⚠️ Risk Profile The strategy, currently has 3 risk profiles ⚠️ patterns for 'fixed percentage exits': Take Profit (%) and Stop Loss (%) . They are: ⚠️ Rich's Profiles ✔️🆑 Conservative: 🎯 TP=2.7 % 🛑 SL=2.7 % ❌Ⓜ️ Moderate: 🎯 TP=2.8 % 🛑 SL=2.7 % ❌🅰 Aggressive: 🎯 TP=1.6 % 🛑 SL=6.9 % You will be able to select and switch between the above options and profiles through the 'input' menu of the strategy by navigating to the "⚠️ Risk Profile" menu. You can then select, test and apply the Risk Profile above that best suits your risk management, expectations and reality , as well as customize all the 'fixed exit' values through the TP and SL menus below. 1️⃣7️⃣ : ⭕ Moving Exits : (Indicators) The strategy currently also has 'Moving Exits' based on indicator signals. These are Moving Exits (Indicators) 📈 LONG : (EXIT) 🧃 (MAO) Short : true 📉 SHORT : (EXIT) 🧃 (MAO) Long: false You can select and toggle between the above options through the 'input' menu of the strategy by navigating to the "LONG : Exit" and "SHORT : Exit" menu. 1️⃣8️⃣ : 💸 Initial Capital By default the "Initial Capital" set for entries and backtests of this strategy is: 10000 $ You can set another value for the 'Starting Capital' through the tradingview menu under "properties" , and edit the value of the "Initial Capital" field. This way you can set and test other 'Entry Values' for your trades, tests and backtests. 1️⃣9️⃣ : ⚙️ Entry Options By default the 'order size' set for this strategy is 100 % of the 'initial capital' on each new trade. You can set and test other entry options like : contracts , cash , % of equity You should make these changes directly in the input menu of the strategy by navigating to the menu "⚙️ Properties : TradingView" below. ⚙️ Properties : (TradingView) 📊 Strategy Type: strategy.position_size != 1 📝💲 % Order Type: % of equity 📝💲 % Order Size: 100 Leverage: 1 So you can define and test other 'Entry Options' for your trades, tests and backtests. 2️⃣0️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Third-Party Services' It is possible to automate the signals of this strategy for any centralized or decentralized broker, as well as for messaging services: Discord, Telegram and Twitter. All in an extremely simple and uncomplicated way through the tutorials available in PDF /VIDEO for our Titan Pro 👽 subscriber community. With our tutorials in PDF and Video it will be possible to automate the signals of this strategy for the chosen service in an extremely simple way with less than 10 steps only. Tradingview naturally doesn't count with native integration between brokers and tradingview. But it is possible to use 'third party services' to do the integration and automation between Tradingview and your centralized or decentralized broker. Here are the standard, available and recommended 'third party services' to automate the signals from the 'Quantitative THEMIS' strategy on the tradingview for your broker: 1) Wundertrading (Recommended): 2) 3commas: 3) Zignaly: 4) Aleeert.com (Recommended): 5) Alertatron: Note! 'Third party services' cannot perform 'withdrawals' via their key 'API', they can only open positions, so your funds will always be 'safe' in your brokerage firm, being traded via the 'API', when they receive an entry and exit signal from this strategy. 2️⃣1️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Exchanges You can automate this strategy for any of the brokers below, through your broker's 'API' by connecting it to the 'third party automation services' for tradingview available and mentioned in the menu above: 1) Binance (Recommended) 2) Bitmex 3) Bybit 4) KuCoin 5) Deribit 6) OKX 7) Coinbase 8) Huobi 9) Bitfinex 10) Bitget 11) Bittrex 12) Bitstamp 13) Gate. io 14) Kraken 15) Gemini 16) Ascendex 17) VCCE 2️⃣2️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Messaging Services' You can also automate and monitor the signals of this strategy much more efficiently by sending them to the following popular messaging services: 1) Discord 2) Telegram 3) Twitter 2️⃣3️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : '🧲🤖Copy-Trading' It will also be possible to copy/replicate the entries and exits of this strategy to your broker in an extremely simple and agile way, through the available copy-trader services. This way it will be possible to replicate the signals of this strategy at each entry and exit to your broker through the API connecting it to the integrated copy-trader services available through the tradingview automation services below: 1) Wundetrading: 2) Zignaly: 2️⃣4️⃣ : ❔ Why be a Titan Pro 👽❔ I believe that today I am at another level in 'pinescript' development. I consider myself today a true unicorn as a pinescript developer, someone unique and very rare. If you choose another tool or another pinescript service, this tool will be just another one, with no real results. But if you join our Titan community, you will have access to a unique tool! And you will get real results! I already earn money consistently with statistical and automated trading and as an expert pinescript developer. I am here to evolve my skills as much as possible, and one day become a pinescript 'Wizard'. So excellence, quality and professionalism will always be my north here. You will never find a developer like me, and who will take so seriously such a revolutionary project as this one. A Maverick! ▬ The man never stops! Here you will find the highest degree of sophistication and development in the market for 'pinescript'. You will get the best of me and the best of pinescript possible. Let me show you how a professional in my field does it. Become a Titan Pro Member 👽 and get Full Access to this strategy and all the Automation Tutorials. Be the Titan in your life! 2️⃣5️⃣ : ❔ Why be a Titan Aff 🛸❔ Get financial return for your referrals, Decentralize the World, and raise the collective consciousness. 2️⃣6️⃣ : 📋 Summary : ⚖️ Strategy: Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h ® Titan Investimentos | Quantitative THEMIS ⚖️ | Demo 🐄 2.6 | Dev: © FilipeSoh 🧙 | 🤖 100% Automated : Discord, Telegram, Twitter, Wundertrading, 3commas, Zignaly, Aleeert, Alertatron, Uniswap-v3 | BINANCE:BTCUSDTPERP 4h 🛒 Subscribe this strategy ❗️ Be a Titan Member 🏛️ 🛒 Titan Pro 👽 🔗 🏛️ Titan Pro 👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) 🛒 Titan Affiliate 🛸 🔗 🏛️ Titan Affiliate 🛸 (Subscription Sale) 🔥 Receive 50% commission 📋 Summary : QT THEMIS ⚖️ 🕵️‍♂️ Check This Strategy..................................................................0 🦄 ® Titan Investimentos...............................................................1 👨‍💻 © Developer..........................................................................2 📚 Signal Automation Tutorials : (PDF/VIDEO).......................................3 👨‍🔧 Revision...............................................................................4 📊 Table : (BACKTEST)..................................................................5 📊 Table : (INFORMATIONS).............................................................6 ⚙️ Properties : (TRADINGVIEW)........................................................7 📆 Backtest : (TRADINGVIEW)..........................................................8 ⚠️ Risk Profile...........................................................................9 🟢 On 🔴 Off : (LONG/SHORT).......................................................10 📈 LONG : (ENTRY)....................................................................11 📉 SHORT : (ENTRY)...................................................................12 📈 LONG : (EXIT).......................................................................13 📉 SHORT : (EXIT)......................................................................14 🧩 (EI) External Indicator.............................................................15 📡 (QT) Quantitative...................................................................16 🎠 (FF) Forecast......................................................................17 🅱 (BB) Bollinger Bands................................................................18 🧃 (MAP) Moving Average Primary......................................................19 🧃 (MAP) Labels.........................................................................20 🍔 (MAQ) Moving Average Quaternary.................................................21 🍟 (MACD) Moving Average Convergence Divergence...............................22 📣 (VWAP) Volume Weighted Average Price........................................23 🪀 (HL) HILO..........................................................................24 🅾 (OBV) On Balance Volume.........................................................25 🥊 (SAR) Stop and Reverse...........................................................26 🛡️ (DSR) Dynamic Support and Resistance..........................................27 🔊 (VD) Volume Directional..........................................................28 🧰 (RSI) Relative Momentum Index.................................................29 🎯 (TP) Take Profit %..................................................................30 🛑 (SL) Stop Loss %....................................................................31 🤖 Automation Selected...............................................................32 📱💻 Discord............................................................................33 📱💻 Telegram..........................................................................34 📱💻 Twitter...........................................................................35 🤖 Wundertrading......................................................................36 🤖 3commas............................................................................37 🤖 Zignaly...............................................................................38 🤖 Aleeert...............................................................................39 🤖 Alertatron...........................................................................40 🤖 Uniswap-v3..........................................................................41 🧲🤖 Copy-Trading....................................................................42 ♻️ ® No Repaint........................................................................43 🔒 Copyright ©️..........................................................................44 🏛️ Be a Titan Member..................................................................45 Nº Active Users..........................................................................46 ⏱ Time Left............................................................................47 | 0 | 🕵️‍♂️ Check This Strategy 🕵️‍♂️ Version Demo: 🐄 Version with ❌non-integrated automation 🤖 and 📚 Tutorials for automation ❌not available 🕵️‍♂️ Version Pro: 👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) | 1 | 🦄 ® Titan Investimentos Decentralizing the World 🗺 Raising the Collective Conscience 🗺 🦄Site: 🦄TradingView: www.tradingview.com 🦄Discord: 🦄Telegram: 🦄Youtube: 🦄Twitter: 🦄Instagram: 🦄TikTok: 🦄Linkedin: 🦄E-mail: | 2 | 👨‍💻 © Developer 🧠 Developer: @FilipeSoh🧙 📺 TradingView: www.tradingview.com ☑️ Linkedin: ✅ Fiverr: ✅ Upwork: 🎥 YouTube: 🐤 Twitter: 🤳 Instagram: | 3 | 📚 Signal Automation Tutorials : (PDF/VIDEO) 📚 Discord: 🔗 Link: 🔒Titan Pro👽 📚 Telegram: 🔗 Link: 🔒Titan Pro👽 📚 Twitter: 🔗 Link: 🔒Titan Pro👽 📚 Wundertrading: 🔗 Link: 🔒Titan Pro👽 📚 3comnas: 🔗 Link: 🔒Titan Pro👽 📚 Zignaly: 🔗 Link: 🔒Titan Pro👽 📚 Aleeert: 🔗 Link: 🔒Titan Pro👽 📚 Alertatron: 🔗 Link: 🔒Titan Pro👽 📚 Uniswap-v3: 🔗 Link: 🔒Titan Pro👽 📚 Copy-Trading: 🔗 Link: 🔒Titan Pro👽 | 4 | 👨‍🔧 Revision 👨‍🔧 Start Of Operations: 01 Jan 2019 21:00 -0300 💡 Start Of Operations (Skin in the game) : Revision 1.0 👨‍🔧 Previous Review: 01 Jan 2022 21:00 -0300 💡 Previous Review : Revision 2.0 👨‍🔧 Current Revision: 01 Jan 2023 21:00 -0300 💡 Current Revision : Revision 2.6 👨‍🔧 Next Revision: 28 May 2023 21:00 -0300 💡 Next Revision : Revision 2.7 | 5 | 📊 Table : (BACKTEST) 📊 Table: true 🖌️ Style: label.style_label_left 📐 Size: size_small 📏 Line: defval 🎨 Color: #131722 | 6 | 📊 Table : (INFORMATIONS) 📊 Table: false 🖌️ Style: label.style_label_right 📐 Size: size_small 📏 Line: defval 🎨 Color: #131722 | 7 | ⚙️ Properties : (TradingView) 📊 Strategy Type: strategy.position_size != 1 📝💲 % Order Type: % of equity 📝💲 % Order Size: 100 % 🚀 Leverage: 1 | 8 | 📆 Backtest : (TradingView) 🗓️ Mon: true 🗓️ Tue: true 🗓️ Wed: true 🗓️ Thu: true 🗓️ Fri: true 🗓️ Sat: true 🗓️ Sun: true 📆 Range: custom 📆 Start: UTC 31 Oct 2008 00:00 📆 End: UTC 31 Oct 2030 23:45 📆 Session: 0000-0000 📆 UTC: UTC | 9 | ⚠️ Risk Profile ✔️🆑 Conservative: 🎯 TP=2.7 % 🛑 SL=2.7 % ❌Ⓜ️ Moderate: 🎯 TP=2.8 % 🛑 SL=2.7 % ❌🅰 Aggressive: 🎯 TP=1.6 % 🛑 SL=6.9 % | 10 | 🟢 On 🔴 Off : (LONG/SHORT) 🟢📈 LONG: true 🟢📉 SHORT: true | 11 | 📈 LONG : (ENTRY) 📡 (QT) Long: true 🧃 (MAP) Long: false 🅱 (BB) Long: false 🍟 (MACD) Long: false 🅾 (OBV) Long: false | 12 | 📉 SHORT : (ENTRY) 📡 (QT) Short: true 🧃 (MAP) Short: false 🅱 (BB) Short: false 🍟 (MACD) Short: false 🅾 (OBV) Short: false | 13 | 📈 LONG : (EXIT) 🧃 (MAP) Short: true | 14 | 📉 SHORT : (EXIT) 🧃 (MAP) Long: false | 15 | 🧩 (EI) External Indicator 🧩 (EI) Connect your external indicator/filter: false 🧩 (EI) Connect your indicator here (Study mode only): close 🧩 (EI) Connect your indicator here (Study mode only): close | 16 | 📡 (QT) Quantitative 📡 (QT) Quantitative: true 📡 (QT) Market: BINANCE:BTCUSDTPERP 📡 (QT) Dice: openai | 17 | 🎠 (FF) Forecast 🎠 (FF) Include current unclosed current candle: true 🎠 (FF) Forecast Type: flat 🎠 (FF) Nº of candles to use in linear regression: 3 | 18 | 🅱 (BB) Bollinger Bands 🅱 (BB) Bollinger Bands: true 🅱 (BB) Type: EMA 🅱 (BB) Period: 20 🅱 (BB) Source: close 🅱 (BB) Multiplier: 2 🅱 (BB) Linewidth: 0 🅱 (BB) Color: #131722 | 19 | 🧃 (MAP) Moving Average Primary 🧃 (MAP) Moving Average Primary: true 🧃 (MAP) BarColor: false 🧃 (MAP) Background: false 🧃 (MAP) Type: SMA 🧃 (MAP) Source: open 🧃 (MAP) Period: 100 🧃 (MAP) Multiplier: 2.0 🧃 (MAP) Linewidth: 2 🧃 (MAP) Color P: #42bda8 🧃 (MAP) Color N: #801922 | 20 | 🧃 (MAP) Labels 🧃 (MAP) Labels: true 🧃 (MAP) Style BUY ZONE: shape.labelup 🧃 (MAP) Color BUY ZONE: #42bda8 🧃 (MAP) Style SELL ZONE: shape.labeldown 🧃 (MAP) Color SELL ZONE: #801922 | 21 | 🍔 (MAQ) Moving Average Quaternary 🍔 (MAQ) Moving Average Quaternary: true 🍔 (MAQ) BarColor: false 🍔 (MAQ) Background: false 🍔 (MAQ) Type: SMA 🍔 (MAQ) Source: close 🍔 (MAQ) Primary: 14 🍔 (MAQ) Secondary: 22 🍔 (MAQ) Tertiary: 44 🍔 (MAQ) Quaternary: 16 🍔 (MAQ) Linewidth: 0 🍔 (MAQ) Color P: #42bda8 🍔 (MAQ) Color N: #801922 | 22 | 🍟 (MACD) Moving Average Convergence Divergence 🍟 (MACD) Macd Type: EMA 🍟 (MACD) Signal Type: EMA 🍟 (MACD) Source: close 🍟 (MACD) Fast: 12 🍟 (MACD) Slow: 26 🍟 (MACD) Smoothing: 9 | 23 | 📣 (VWAP) Volume Weighted Average Price 📣 (VWAP) Source: close 📣 (VWAP) Period: 340 📣 (VWAP) Momentum A: 84 📣 (VWAP) Momentum B: 150 📣 (VWAP) Average Volume: 1 📣 (VWAP) Multiplier: 1 📣 (VWAP) Diviser: 2 | 24 | 🪀 (HL) HILO 🪀 (HL) Type: SMA 🪀 (HL) Function: Maverick🧙 🪀 (HL) Source H: high 🪀 (HL) Source L: low 🪀 (HL) Period: 20 🪀 (HL) Momentum: 26 🪀 (HL) Diviser: 2 🪀 (HL) Multiplier: 1 | 25 | 🅾 (OBV) On Balance Volume 🅾 (OBV) Type: EMA 🅾 (OBV) Source: close 🅾 (OBV) Period: 16 🅾 (OBV) Diviser: 2 🅾 (OBV) Multiplier: 1 | 26 | 🥊 (SAR) Stop and Reverse 🥊 (SAR) Source: close 🥊 (SAR) High: 1.8 🥊 (SAR) Mid: 1.6 🥊 (SAR) Low: 1.6 🥊 (SAR) Diviser: 2 🥊 (SAR) Multiplier: 1 | 27 | 🛡️ (DSR) Dynamic Support and Resistance 🛡️ (DSR) Source D: close 🛡️ (DSR) Source R: high 🛡️ (DSR) Source S: low 🛡️ (DSR) Momentum R: 0 🛡️ (DSR) Momentum S: 2 🛡️ (DSR) Diviser: 2 🛡️ (DSR) Multiplier: 1 | 28 | 🔊 (VD) Volume Directional 🔊 (VD) Type: SMA 🔊 (VD) Period: 68 🔊 (VD) Momentum: 3.8 🔊 (VD) Diviser: 2 🔊 (VD) Multiplier: 1 | 29 | 🧰 (RSI) Relative Momentum Index 🧰 (RSI) Type UP: EMA 🧰 (RSI) Type DOWN: EMA 🧰 (RSI) Source: close 🧰 (RSI) Period: 29 🧰 (RSI) Smoothing: 22 🧰 (RSI) Momentum R: 64 🧰 (RSI) Momentum S: 142 🧰 (RSI) Diviser: 2 🧰 (RSI) Multiplier: 1 | 30 | 🎯 (TP) Take Profit % 🎯 (TP) Take Profit: false 🎯 (TP) %: 2.2 🎯 (TP) Color: #42bda8 🎯 (TP) Linewidth: 1 | 31 | 🛑 (SL) Stop Loss % 🛑 (SL) Stop Loss: false 🛑 (SL) %: 2.7 🛑 (SL) Color: #801922 🛑 (SL) Linewidth: 1 | 32 | 🤖 Automation : Discord | Telegram | Twitter | Wundertrading | 3commas | Zignaly | Aleeert | Alertatron | Uniswap-v3 🤖 Automation Selected : Discord | 33 | 🤖 Discord 🔗 Link Discord: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Discord ▬ Enter Long: 🔒Titan Pro👽 📱💻 Discord ▬ Exit Long: 🔒Titan Pro👽 📱💻 Discord ▬ Enter Short: 🔒Titan Pro👽 📱💻 Discord ▬ Exit Short: 🔒Titan Pro👽 | 34 | 🤖 Telegram 🔗 Link Telegram: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Telegram ▬ Enter Long: 🔒Titan Pro👽 📱💻 Telegram ▬ Exit Long: 🔒Titan Pro👽 📱💻 Telegram ▬ Enter Short: 🔒Titan Pro👽 📱💻 Telegram ▬ Exit Short: 🔒Titan Pro👽 | 35 | 🤖 Twitter 🔗 Link Twitter: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Twitter ▬ Enter Long: 🔒Titan Pro👽 📱💻 Twitter ▬ Exit Long: 🔒Titan Pro👽 📱💻 Twitter ▬ Enter Short: 🔒Titan Pro👽 📱💻 Twitter ▬ Exit Short: 🔒Titan Pro👽 | 36 | 🤖 Wundertrading : Binance | Bitmex | Bybit | KuCoin | Deribit | OKX | Coinbase | Huobi | Bitfinex | Bitget 🔗 Link Wundertrading: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Wundertrading ▬ Enter Long: 🔒Titan Pro👽 📱💻 Wundertrading ▬ Exit Long: 🔒Titan Pro👽 📱💻 Wundertrading ▬ Enter Short: 🔒Titan Pro👽 📱💻 Wundertrading ▬ Exit Short: 🔒Titan Pro👽 | 37 | 🤖 3commas : Binance | Bybit | OKX | Bitfinex | Coinbase | Deribit | Bitmex | Bittrex | Bitstamp | Gate.io | Kraken | Gemini | Huobi | KuCoin 🔗 Link 3commas: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 3commas ▬ Enter Long: 🔒Titan Pro👽 📱💻 3commas ▬ Exit Long: 🔒Titan Pro👽 📱💻 3commas ▬ Enter Short: 🔒Titan Pro👽 📱💻 3commas ▬ Exit Short: 🔒Titan Pro👽 | 38 | 🤖 Zignaly : Binance | Ascendex | Bitmex | Kucoin | VCCE 🔗 Link Zignaly: 🔗 Link 📚 Automation: 🔒Titan Pro👽 🤖 Type Automation: Profit Sharing 🤖 Type Provider: Webook 🔑 Key: 🔒Titan Pro👽 🤖 pair: BTCUSDTP 🤖 exchange: binance 🤖 exchangeAccountType: futures 🤖 orderType: market 🚀 leverage: 1x % positionSizePercentage: 100 % 💸 positionSizeQuote: 10000 $ 🆔 signalId: @Signal1234 | 39 | 🤖 Aleeert : Binance 🔗 Link Aleeert: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Aleeert ▬ Enter Long: 🔒Titan Pro👽 📱💻 Aleeert ▬ Exit Long: 🔒Titan Pro👽 📱💻 Aleeert ▬ Enter Short: 🔒Titan Pro👽 📱💻 Aleeert ▬ Exit Short: 🔒Titan Pro👽 | 40 | 🤖 Alertatron : Binance | Bybit | Deribit | Bitmex 🔗 Link Alertatron: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Alertatron ▬ Enter Long: 🔒Titan Pro👽 📱💻 Alertatron ▬ Exit Long: 🔒Titan Pro👽 📱💻 Alertatron ▬ Enter Short: 🔒Titan Pro👽 📱💻 Alertatron ▬ Exit Short: 🔒Titan Pro👽 | 41 | 🤖 Uniswap-v3 🔗 Link Alertatron: 🔗 Link 📚 Automation: 🔒Titan Pro👽 📱💻 Uniswap-v3 ▬ Enter Long: 🔒Titan Pro👽 📱💻 Uniswap-v3 ▬ Exit Long: 🔒Titan Pro👽 📱💻 Uniswap-v3 ▬ Enter Short: 🔒Titan Pro👽 📱💻 Uniswap-v3 ▬ Exit Short: 🔒Titan Pro👽 | 42 | 🧲🤖 Copy-Trading : Zignaly | Wundertrading 🔗 Link 📚 Copy-Trading: 🔒Titan Pro👽 🧲🤖 Copy-Trading ▬ Zignaly: 🔒Titan Pro👽 🧲🤖 Copy-Trading ▬ Wundertrading: 🔒Titan Pro👽 | 43 | ♻️ ® Don't Repaint! ♻️ This Strategy does not Repaint!: ® Signs Do not repaint❕ ♻️ This is a Real Strategy!: Quality : ® Titan Investimentos 📋️️ Get more information about Repainting here: | 44 | 🔒 Copyright ©️ 🔒 Copyright ©️: Copyright © 2023-2024 All rights reserved, ® Titan Investimentos 🔒 Copyright ©️: ® Titan Investimentos 🔒 Copyright ©️: Unique and Exclusive Strategy. All rights reserved | 45 | 🏛️ Be a Titan Members 🏛️ Titan Pro 👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) 🏛️ Titan Affiliate 🛸 (Subscription Sale) 🔥 Receive 50% commission | 46 | ⏱ Time Left Time Left Titan Demo 🐄: ⏱♾ | ⏱ : ♾ Titan Demo 🐄 Version with ❌non-integrated automation 🤖 and 📚 Tutorials for automation ❌not available Time Left Titan Pro 👽: 🔒Titan Pro👽 | ⏱ : Pro Plans: 30 Days, 90 Days, 12 Months, 24 Months. (👽 Pro 🅼 Monthly, 👽 Pro 🆀 Quarterly, 👽 Pro🅰 Annual, 👽 Pro👾Two Years) | 47 | Nº Active Users Nº Active Subscribers Titan Pro 👽: 5️⃣6️⃣ | 1✔️ 5✔️ 10✔️ 100❌ 1K❌ 10K❌ 50K❌ 100K❌ 1M❌ 10M❌ 100M❌ : ⏱ Active Users is updated every 24 hours (Check on indicator) Nº Active Affiliates Titan Aff 🛸: 6️⃣ | 1✔️ 5✔️ 10❌ 100❌ 1K❌ 10K❌ 50K❌ 100K❌ 1M❌ 10M❌ 100M❌ : ⏱ Active Users is updated every 24 hours (Check on indicator) 2️⃣7️⃣ : 📊 PERFORMANCE : 🆑 Conservative 📊 Exchange: Binance 📊 Pair: BINANCE: BTCUSDTPERP 📊 TimeFrame: 4h 📊 Initial Capital: 10000 $ 📊 Order Type: % equity 📊 Size Per Order: 100 % 📊 Commission: 0.03 % 📊 Pyramid: 1 • ⚠️ Risk Profile: 🆑 Conservative: 🎯 TP=2.7 % | 🛑 SL=2.7 % • 📆All years: 🆑 Conservative: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars: 7325 Net Profit: 🟢 + 1669.89 % 💲 + 166989.43 USD Total Close Trades: ⚪️ 369 Percent Profitable: 🟡 64.77 % Profit Factor: 🟢 2.314 DrawDrown Maximum: 🔴 -24.82 % 💲 -10221.43 USD Avg Trade: 💲 + 452.55 USD ✔️ Trades Winning: 239 ❌ Trades Losing: 130 ✔️ Average Gross Win: + 12.31 % ❌ Average Gross Loss: - 9.78 % ✔️ Maximum Consecutive Wins: 9 ❌ Maximum Consecutive Losses: 6 % Average Gain Annual: 499.33 % % Average Gain Monthly: 41.61 % % Average Gain Weekly: 9.6 % % Average Gain Day: 1.37 % 💲 Average Gain Annual: 49933 $ 💲 Average Gain Monthly: 4161 $ 💲 Average Gain Weekly: 960 $ 💲 Average Gain Day: 137 $ • 📆 Year: 2020: 🆑 Conservative: 🚀 Leverage 1️⃣x • 📆 Year: 2021: 🆑 Conservative: 🚀 Leverage 1️⃣x • 📆 Year: 2022: 🆑 Conservative: 🚀 Leverage 1️⃣x 2️⃣8️⃣ : 📊 PERFORMANCE : Ⓜ️ Moderate 📊 Exchange: Binance 📊 Pair: BINANCE: BTCUSDTPERP 📊 TimeFrame: 4h 📊 Initial Capital: 10000 $ 📊 Order Type: % equity 📊 Size Per Order: 100 % 📊 Commission: 0.03 % 📊 Pyramid: 1 • ⚠️ Risk Profile: Ⓜ️ Moderate: 🎯 TP=2.8 % | 🛑 SL=2.7 % • 📆 All years: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars: 7325 Net Profit: 🟢 + 1472.04 % 💲 + 147199.89 USD Total Close Trades: ⚪️ 362 Percent Profitable: 🟡 63.26 % Profit Factor: 🟢 2.192 DrawDrown Maximum: 🔴 -22.69 % 💲 -9269.33 USD Avg Trade: 💲 + 406.63 USD ✔️ Trades Winning: 229 ❌ Trades Losing : 133 ✔️ Average Gross Win: + 11.82 % ❌ Average Gross Loss: - 9.29 % ✔️ Maximum Consecutive Wins: 9 ❌ Maximum Consecutive Losses: 8 % Average Gain Annual: 440.15 % % Average Gain Monthly: 36.68 % % Average Gain Weekly: 8.46 % % Average Gain Day: 1.21 % 💲 Average Gain Annual: 44015 $ 💲 Average Gain Monthly: 3668 $ 💲 Average Gain Weekly: 846 $ 💲 Average Gain Day: 121 $ • 📆 Year: 2020: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x • 📆 Year: 2021: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x • 📆 Year: 2022: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x 2️⃣9️⃣ : 📊 PERFORMANCE : 🅰 Aggressive 📊 Exchange: Binance 📊 Pair: BINANCE: BTCUSDTPERP 📊 TimeFrame: 4h 📊 Initial Capital: 10000 $ 📊 Order Type: % equity 📊 Size Per Order: 100 % 📊 Commission: 0.03 % 📊 Pyramid: 1 • ⚠️ Risk Profile: 🅰 Aggressive: 🎯 TP=1.6 % | 🛑 SL=6.9 % • 📆 All years: 🅰 Aggressive: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars: 7325 Net Profit: 🟢 + 989.38 % 💲 + 98938.38 USD Total Close Trades: ⚪️ 380 Percent Profitable: 🟢 84.47 % Profit Factor: 🟢 2.156 DrawDrown Maximum: 🔴 -17.88 % 💲 -9182.84 USD Avg Trade: 💲 + 260.36 USD ✔️ Trades Winning: 321 ❌ Trades Losing: 59 ✔️ Average Gross Win: + 5.75 % ❌ Average Gross Loss: - 14.51 % ✔️ Maximum Consecutive Wins: 21 ❌ Maximum Consecutive Losses: 6 % Average Gain Annual: 295.84 % % Average Gain Monthly: 24.65 % % Average Gain Weekly: 5.69 % % Average Gain Day: 0.81 % 💲 Average Gain Annual: 29584 $ 💲 Average Gain Monthly: 2465 $ 💲 Average Gain Weekly: 569 $ 💲 Average Gain Day: 81 $ • 📆 Year: 2020: 🅰 Aggressive: 🚀 Leverage 1️⃣x • 📆 Year: 2021: 🅰 Aggressive: 🚀 Leverage 1️⃣x • 📆 Year: 2022: 🅰 Aggressive: 🚀 Leverage 1️⃣x 3️⃣0️⃣ : 🛠️ Roadmap 🛠️• 14/ 01 /2023 : Titan THEMIS Launch 🛠️• Updates January/2023 : • 📚 Tutorials for Automation 🤖 already Available : ✔️ • ✔️ Discord • ✔️ Wundertrading • ✔️ Zignaly • 📚 Tutorials for Automation 🤖 In Preparation : ⭕ • ⭕ Telegram • ⭕ Twitter • ⭕ 3comnas • ⭕ Aleeert • ⭕ Alertatron • ⭕ Uniswap-v3 • ⭕ Copy-Trading 🛠️• Updates February/2023 : • 📰 Launch of advertising material for Titan Affiliates 🛸 • 🛍️🎥🖼️📊 (Sales Page/VSL/Videos/Creative/Infographics) 🛠️• 28/05/2023 : Titan THEMIS update ▬ Version 2.7 🛠️• 28/05/2023 : BOT BOB release ▬ Version 1.0 • (Native Titan THEMIS Automation - Through BOT BOB, a bot for automation of signals, indicators and strategies of TradingView, of own code ▬ in validation. • BOT BOB Automation/Connection : • API - For Centralized Brokers. • Smart Contracts - Wallet Web - For Decentralized Brokers. • This way users can automate any indicator or strategy of TradingView and Titan in a decentralized, secure and simplified way. • Without having the need to use 'third party services' for automating TradingView indicators and strategies like the ones available above. 🛠️• 28/05/2023 : Release ▬ Titan Culture Guide 📝 3️⃣1️⃣ : 🧻 Notes ❕ 🧻 • Note ❕ The "Demo 🐄" version, ❌does not have 'integrated automation', to automate the signals of this strategy and enjoy a fully automated system, you need to have access to the Pro version with '100% integrated automation' and all the tutorials for automation available. Become a Titan Pro 👽 🧻 • Note ❕ You will also need to be a "Pro User or higher on Tradingview", to be able to use the webhook feature available only for 'paid' profiles on the platform. With the webhook feature it is possible to send the signals of this strategy to almost anywhere, in our case to centralized or decentralized brokerages, also to popular messaging services such as: Discord, Telegram or Twiter. 3️⃣2️⃣ : 🚨 Disclaimer ❕❗ 🚨 • Disclaimer ❕❕ Past positive result and performance of a system does not guarantee its positive result and performance for the future! 🚨 • Disclaimer ❗❗❗ When using this strategy: Titan Investments is totally Exempt from any claim of liability for losses. The responsibility on the management of your funds is solely yours. This is a very high risk/volatility market! Understand your place in the market. 3️⃣3️⃣ : ♻️ ® No Repaint This Strategy does not Repaint! This is a real strategy! 3️⃣4️⃣ : 🔒 Copyright ©️ Copyright © 2022-2023 All rights reserved, ® Titan Investimentos 3️⃣5️⃣ : 👏 Acknowledgments I want to start this message in thanks to TradingView and all the Pinescript community for all the 'magic' created here, a unique ecosystem! rich and healthy, a fertile soil, a 'new world' of possibilities, for a complete deepening and improvement of our best personal skills. I leave here my immense thanks to the whole community: Tradingview, Pinecoders, Wizards and Moderators. I was not born Rich . Thanks to TradingView and pinescript and all its transformation. I could develop myself and the best of me and the best of my skills. And consequently build wealth and patrimony. Gratitude. One more story for the infinite book ! If you were born poor you were born to be rich ! Raising🔼 the level and raising🔼 the ruler! 📏 My work is my 'debauchery'! Do better! 💐🌹 Soul of a first-timer! Creativity Exudes! 🦄 This is the manifestation of God's magic in me. This is the best of me. 🧙 You will copy me, I know. So you owe me. 💋 My mission here is to raise the consciousness and self-esteem of all Titans and Titanids! Welcome! 🧘 🏛️ The only way to accomplish great work is to do what you love ! Before I learned to program I was wasting my life! Death is the best creation of life . Now you are the new , but in the not so distant future you will gradually become the old . Here I stay forever! Playing the game like an Athlete! 🖼️ Enjoy and Enjoy 🍷 🗿 In honor of: BOB ☆ 1 name, 3 letters, 3 possibilities, and if read backwards it's the same thing, a palindrome. ☘ Gratitude to the oracles that have enabled me the 'luck' to get this far: Dal&Ni&Fer 3️⃣6️⃣ : 👮 House Rules : 📺 TradingView House Rules : This publication and strategy follows all TradingView house guidelines and rules: 📺 TradingView House Rules: www.tradingview.com 📺 Script publication rules: www.tradingview.com 📺 Vendor requirements: www.tradingview.com 📺 Links/References rules: www.tradingview.com 3️⃣7️⃣ : 🏛️ Become a Titan Pro member 👽 🟩 Titan Pro 👽 🟩 3️⃣8️⃣ : 🏛️ Be a member Titan Aff 🛸 🟥 Titan Affiliate 🛸 🟥

Strategi Pine Script®

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Multi-Market Swing Trader Webhook Ready [HullBuster] Introduction This is an all symbol swing trading strategy intended for webhook integration to live accounts. This script employs an adjustable bandwidth ping pong algorithm which can be run in long only, short only or bidirectional modes. Additionally, this script provides advanced features such as pyramiding and DCA. It has been in development for nearly three years and exposes over 90 inputs to accommodate varying risk reward ratios. Equipped with a proper configuration it is suitable for professional traders seeking quality trades from a cloud based platform. This is my most advanced Pine Script to date which combines my RangeV3 and TrendV2 scripts. Using this combination it tries to bridge the gap between range bound and trending markets. I have put a lot of time into creating a system that could transition by itself so as to require less human intervention and thus be able to withstand long periods in full automation mode. As a Pine strategy, hypothetical performance can be easily back-tested. Allowing you to Iron out the configuration of your target instrument. Now with recent advancements from the Pine development team this same script can be connected to a webhook through the alert mechanism. The requirement of a separate study script has been completely removed. This really makes things a lot easier to get your trading system up and running. I would like to also mention that TradingView has made significant advancements to the back-end over the last year. Notably, compile times are much faster now permitting more complex algorithms to be implemented. Thank you TradingView! I used QuantConnect as my role model and strived to produce a base script which could compete with higher end cloud based platforms while being attractive to similarly experienced traders. The versatility of the Pine Language combined with the greater selection of end point execution systems provides a powerful alternative to other cloud based platforms. At the very least, with the features available today, a modular trading system for everyday use is a reality. I hope you'll agree. This is a swing trading strategy so the behavior of this script is to buy on weakness and sell on strength. In trading parlance this is referred to as Support and Resistance Trading. Support being the point at which prices stop falling and start rising. Resistance being the point at which prices stop rising and fall. The chart real estate between these two points being defined as the range. This script seeks to implement strategies to profit from placing trades within this region. Short positions at resistance and long positions at support. Just to be clear, the range as well as trends are merely illusions as the chart only receives prices. However, this script attempts to calculate pivot points from the price stream. Rising pivots are shorts and falling pivots are longs. I refer to pivots as a vertex in this script which adds structural components to the chart formation (point, sides and a base). When trading in “Ping Pong” mode long and short positions are interleaved continuously as long as there exists a detectable vertex. This is a non-hedging script so those of us subject to NFA FIFO Rule 2-43(b) should be generally safe to webhook into signals emitted from this script. However, as covered later in this document, there are some technical limitations to this statement. I have tested this script on various instruments for over two years and have configurations for forex, crypto and stocks. This script along with my TrendV2 script are my daily trading vehicles as a webhook into my forex and crypto accounts. This script employs various high risk features that could wipe out your account if not used judiciously. You should absolutely not use this script if you are a beginner or looking for a get-rich-quick strategy. Also please see my CFTC RULE 4.41 disclosure statement at the end of the document. Really! Does this script repaint? The short answer is yes, it does, despite my best efforts to the contrary. EMAs are central to my strategy and TradingView calculates from the beginning of the series so there is just no getting around this. However, Pine is improving everyday and I am hopeful that this issue will be address from an architectural level at some point in the future. I have programmed my webhook to compensate for this occurrence so, in the mean time, this my recommended way to handle it (at the endpoint and before the broker). Design This strategy uses a ping pong algorithm of my own design. Basically, trades bounce off each other along the price stream. Trades are produced as a series of reversals. The point at which a trade reverses is a pivot calculation. A measurement is made between the recent valley to peak which results in a standard deviation value. This value is an input to implied probability calculation.Yes, the same implied probability used in sports betting. Odds are then calculated to determine the likelihood of price action continuing or retracing to the pivot. Based on where the account is at alert time, the action could be an entry, take profit or pyramid signal. In this design, trades must occur in alternating sequence. A long followed by a short then another long followed by a short and so on. In range bound price action trades appear along the outer bands of the channel in the aforementioned sequence. Shorts on the top and longs at the bottom. Generally speaking, the widths of the trading bands can be adjusted using the vertex dynamics in Section 2. There are a dozen inputs in this section used to describe the trading range. It is not a simple adjustment. If pyramids are enabled the strategy overrides the ping pong reversal pattern and begins an accumulation sequence. In this case you will see a series of same direction trades. This script uses twelve indicators on a single time frame. The original trading algorithms are a port from a C++ program on proprietary trading platform. I’ve converted some of the statistical functions to use standard indicators available on TradingView. The setups make heavy use of the Hull Moving Average in conjunction with EMAs that form the Bill Williams Alligator as described in his book “New Trading Dimensions” Chapter 3. Lag between the Hull and the EMAs play a key role in identifying the pivot points. I really like the Hull Moving Average. I use it in all my systems, including 3 other platforms. It’s is an excellent leading indicator and a relatively light calculation. The trend detection algorithms rely on several factors: 1. Smoothed EMAs in a Willams Alligator pattern. 2. Number of pivots encountered in a particular direction. 3. Which side debt is being incurred. 4. Settings in Section 4 and 5 (long and short) The strategy uses these factors to determine the probability of prices continuing in the most recent direction. My TrendV2 script uses a higher time frame to determine trend direction. I can’t use that method in this script without exceeding various TradingView limitations on code size. However, the higher time frame is the best way to know which trend is worth pursuing or better to bet against. The entire script is around 2400 lines of Pine code which pushes the limits of what can be created on this platform given the TradingView maximums for: local scopes, run-time duration and compile time. The module has been through numerous refactoring passes and makes extensive use of ternary statements. As such, It takes a full minute to compile after adding it to a chart. Please wait for the hovering dots to disappear before attempting to bring up the input dialog box. Scrolling the chart quickly may bring up an hour glass. Regardless of the market conditions: range or trend. The behavior of the script is governed entirely by the 91 inputs. Depending on the settings, bar interval and symbol, you can configure a system to trade in small ranges producing a thousand or more trades. If you prefer wider ranges with fewer trades then the vertex detection settings in Section 2 should employ stiffer values. To make the script more of a trend follower, adjustments are available in Section 4 and 5 (long and short respectively). Overall this script is a range trader and the setups want to get in that way. It cannot be made into a full blown trend trading system. My TrendV2 is equipped for that purpose. Conversely, this script cannot be effectively deployed as a scalper either. The vertex calculation require too much data for high frequency trading. That doesn’t work well for retail customers anyway. The script is designed to function in bar intervals between 5 minutes and 4 hours. However, larger intervals require more backtest data in order to create reliable configurations. TradingView paid plans (Pro) only provide 10K bars which may not be sufficient. Please keep that in mind. The transition from swing trader to trend follower typically happens after a stop is hit. That means that your account experiences a loss first and usually with a pyramid stack so the loss could be significant. Even then the script continues to alternate trades long and short. The difference is that the strategy tries to be more long on rising prices and more short on falling prices as opposed to simply counter trend trading. Otherwise, a continuous period of rising prices results in a distinctly short pyramid stack. This is much different than my TrendV2 script which stays long on peaks and short on valleys. Basically, the plan is to be profitable in range bound markets and just lose less when a trend comes along. How well this actually plays out will depend largely on the choices made in the sectioned input parameters. Sections The input dialog for this script contains 91 inputs separated into six sections. Section 1: Global settings for the strategy including calculation model, trading direction, exit levels, pyramid and DCA settings. This is where you specify your minimum profit and stop levels. You should setup your Properties tab inputs before working on any of the sections. It’s really important to get the Base Currency right before doing any work on the strategy inputs. It is important to understand that the “Minimum Profit” and “Limit Offset” are conditional exits. To exit at a profit, the specified value must be exceeded during positive price pressure. On the other hand, the “Stop Offset” is a hard limit. Section 2: Vertex dynamics. The script is equipped with four types of pivot point indicators. Histogram, candle, fractal and transform. Despite how the chart visuals may seem. The chart only receives prices. It’s up to the strategy to interpret patterns from the number stream. The quality of the feed and the symbol’s bar characteristics vary greatly from instrument to instrument. Each indicator uses a fundamentally different pattern recognition algorithm. Use trial and error to determine the best fit for your configuration. After selecting an indicator type, there are eight analog fields that must be configured for that particular indicator. This is the hardest part of the configuration process. The values applied to these fields determine how the range will be measured. They have a big effect on the number of trades your system will generate. To see the vertices click on the “Show Markers” check box in this section. Red markers are long positions and blue markers are short. This will give you an idea of where trades will be placed in natural order. Section 3: Event thresholds. Price spikes are used to enter and exit trades. The magnitude which define these spikes are configured here. The rise and fall events are primarily for pyramid placement. The rise and fall limits determine the exit threshold for the conditional “Limit Offset” field found in Section 1. These fields should be adjusted one at a time. Use a zero value to disengage every one but the one you are working on. Use the fill colors found in Section 6 to get a visual on the values applied to these fields. To make it harder for pyramids to enter stiffen the Event values. This is more of a hack as the formal pyramid parameters are in Section 1. Section 4 and 5: Long and short settings. These are mirror opposite settings with all opposing fields having the same meaning. Its really easy to introduce data mining bias into your configuration through these fields. You must combat against this tendency by trying to keep your settings as uniform as possible. Wildly different parameters for long and short means you have probably fitted the chart. There are nine analog and thirteen Boolean fields per trade direction. This section is all about how the trades themselves will be placed along the range defined in Section 2. Generally speaking, more restrictive settings will result in less trades but higher quality. Remember that this strategy will enter long on falling prices and short on rising prices. So getting in the trade too early leads to a draw-down. However, this could be what you want if pyramiding is enabled. I, personally, have found that the best configurations come from slightly skewing one side. I just accept that the other side will be sub-par. Section 6: Chart rendering. This section contains one analog and four Boolean fields. More or less a diagnostic tool. Of particular interest is the “Symbol Debt Sequence” field. This field contains a whole number which paints regions that have sustained a run of bad trades equal or greater than specified value. It is useful when DCA is enabled. In this script Dollar Cost Averaging on new positions continues only until the symbol debt is recouped. To get a better understanding on how this works put a number in this field and activate DCA. You should notice how the trade size increases in the colored regions. The “Summary Report” checkbox displays a blue information box at the live end of the chart. It exposes several metrics which you may find useful if manually trading this strategy from audible alerts or text messages. Pyramids This script features a downward pyramiding strategy which increases your position size on losing trades. On purely margin trades, this feature can be used to, hypothetically, increase the profit factor of positions (not individual trades). On long only markets, such as crypto, you can use this feature to accumulate coins at depressed prices. The way it works is the stop offset, applied in the Section 1 inputs, determines the maximum risk you intend to bear. Additional trades will be placed at pivot points calculated all the way down to the stop price. The size of each add on trade is increased by a multiple of its interval. The maximum number of intervals is limited by the “Pyramiding” field in the properties tab. The rate at which pyramid positions are created can be adjusted in Section 1. To see the pyramids click on the “Mark Pyramid Levels” check box in the same section. Blue triangles are painted below trades other than the primary. Unlike traditional Martingale strategies, the result of your trade is not dependent on the profit or loss from the last trade. The position must recover the R1 point in order to close. Alternatively, you can set a “Pyramid Bale Out Offset” in Section 1 which will terminate the trade early. However, the bale out must coincide with a pivot point and result in a profitable exit in order to actually close the trade. Should the market price exceed the stop offset set in Section 1, the full value of the position, multiplied by the accepted leverage, will be realized as a loss to the trading account. A series of such losses will certainly wipe out your account. Pyramiding is an advanced feature intended for professional traders with well funded accounts and an appropriate mindset. The availability of this feature is not intended to endorse or promote my use of it. Use at your own risk (peril). DCA In addition to pyramiding this script employs DCA which enables users to experiment with loss recovery techniques. This is another advanced feature which can increase the order size on new trades in response to stopped out or winning streak trades. The script keeps track of debt incurred from losing trades. When the debt is recovered the order size returns to the base amount specified in the properties tab. The inputs for this feature are found in section 3 and include a limiter to prevent your account from depleting capital during runaway markets. The main difference between DCA and pyramids is that this implementation of DCA applies to new trades while pyramids affect open positions. DCA is a popular feature in crypto trading but can leave you with large “bags” if your not careful. In other markets, especially margin trading, you’ll need a well funded account and much experience. To be sure pyramiding and dollar cost averaging is as close to gambling as you can get in respectable trading exchanges. However, if you are looking to compete in a spot trading contest or just want to add excitement to your trading life style those features could find a place in your strategies. Although your backtest may show spectacular gains don’t expect your live trading account to do the same. Every backtest has some measure of data mining bias. Please remember that. Webhook Integration The TradingView alerts dialog provides a way to connect your script to an external system which could actually execute your trade. This is a fantastic feature that enables you to separate the data feed and technical analysis from the execution and reporting systems. Using this feature it is possible to create a fully automated trading system entirely on the cloud. Of course, there is some work to get it all going in a reliable fashion. To that end this script has several things going for it. First off, it is a strategy type script. That means that the strategy place holders such as {{strategy.position_size}} can be embedded in the alert message text. There are more than 10 variables which can write internal script values into the message for delivery to the specified endpoint. Additionally, my scripts output the current win streak and debt loss counts in the {{strategy.order.alert_message}} field. Depending on the condition, this script will output other useful values in the JSON “comment” field of the alert message. Here is an excerpt of the fields I use in my webhook signal: "broker_id": "kraken", "account_id": "XXX XXXX XXXX XXXX", "symbol_id": "XMRUSD", "action": "{{strategy.order.action}}", "strategy": "{{strategy.order.id}}", "lots": "{{strategy.order.contracts}}", "price": "{{strategy.order.price}}", "comment": "{{strategy.order.alert_message}}", "timestamp": "{{time}}" Though TradingView does a great job in dispatching your alert this feature does come with a few idiosyncrasies. Namely, a single transaction call in your script may cause multiple transmissions to the endpoint. If you are using placeholders each message describes part of the transaction sequence. A good example is closing a pyramid stack. Although the script makes a single strategy.close() call, the endpoint actually receives a close message for each pyramid trade. The broker, on the other hand, only requires a single close. The incongruity of this situation is exacerbated by the possibility of messages being received out of sequence. Depending on the type of order designated in the message, a close or a reversal. This could have a disastrous effect on your live account. This broker simulator has no idea what is actually going on at your real account. Its just doing the job of running the simulation and sending out the computed results. If your TradingView simulation falls out of alignment with the actual trading account lots of really bad things could happen. Like your script thinks your are currently long but the account is actually short. Reversals from this point forward will always be wrong with no one the wiser. Human intervention will be required to restore congruence. But how does anyone find out this is occurring? In closed systems engineering this is known as entropy. In practice your webhook logic should be robust enough to detect these conditions. Be generous with the placeholder usage and give the webhook code plenty of information to compare states. Both issuer and receiver. Don’t blindly commit incoming signals without verifying system integrity. Operation This is a swing trading strategy so the fundamental behavior of this script is to buy on weakness and sell on strength. As such trade orders are placed in a counter direction to price pressure. What you will see on the chart is a short position on peaks and a long position on valleys. This is slightly misleading since a range as well as a trend are best recognized, in hindsight, after the patterns occur on the chart. In the middle of a trade, one never knows how deep valleys will drop or how high peaks will rise. For certain, long trades will continue to trigger as the market prices fall and short trades on rising prices. This means that the maximum efficiency of this strategy is achieved in choppy markets where the price doesn’t extend very far from its adjacent pivot point. Conversely, this strategy will be the least efficient when market conditions exhibit long continuous single direction price pressure. Especially, when measured in weeks. Translation, the trend is not your friend with this strategy. Internally, the script attempts to recognize prolonged price pressure and changes tactics accordingly. However, at best, the goal is to weather the trend until the range bound market returns. At worst, trend detection fails and pyramid trades continue to be placed until the limit specified in the Properties tab is reached. In all likelihood this could trigger a margin call and if it hits the stop it could wipe out your account. This script has been in beta test four times since inception. During all that time no one has been successful in creating a configuration from scratch. Most people give up after an hour or so. To be perfectly honest, the configuration process is a bear. I know that but there is no way, currently, to create libraries in Pine. There is also no way specify input parameters other than the flattened out 2-D inputs dialog. And the publish rules clearly state that script variations addressing markets or symbols (suites) are not permitted. I suppose the problem is systemic to be-all-end-all solutions like my script is trying to be. I needed a cloud strategy for all the symbols that I trade and since Pine does not support library modules, include files or inter process communication this script and its unruly inputs are my weapon of choice in the war against the market forces. It takes me about six hours to configure a new symbol. Also not all the symbols I configure are equally successful. I should mention that I have a facsimile of this strategy written in another platform which allows me to run a backtest on 10 years of historical data. The results provide me a sanity check on the inputs I select on this platform. My personal configurations use a 10 minute bar interval on forex instruments and 15 minutes on crypto. I try to align my TradingView scripts to employ standard intervals available from the broker so that I can backtest longer durations than those available on TradingView. For example, Bitcoin at 15 minute bars is downloadable from several sources. I really like the 10 minute bar. It provides lots of detectable patterns and is easy to store many years in an SQL database. The following steps provide a very brief set of instructions that will get you started but will most certainly not produce the best backtest. A trading system that you are willing to risk your hard earned capital will require a well crafted configuration that involves time, expertise and clearly defined goals. As previously mentioned, I have several example configurations that I use for my own trading that I can share with you if you like. To get hands on experience in setting up your own symbol from scratch please follow the steps below. Step 1. Setup the Base currency and order size in the properties tab. Step 2. Select the calculation presets in the Instrument Type field. Step 3. Select “No Trade” in the Trading Mode field Step 4. Select the Histogram indicator from Section 2. You will be experimenting with different ones so it doesn’t matter which one you try first. Step 5. Turn on Show Markers in Section 2. Step 6. Go to the chart and checkout where the markers show up. Blue is up and red is down. Long trades show up along the red markers and short trades on the blue. Step 7. Make adjustments to “Base To Vertex” and “Vertex To Base” net change and ROC in Section 2. Use these fields to move the markers to where you want trades to be. Step 8. Try a different indicator from Section 2 and repeat Step 7 until you find the best match for this instrument on this interval. This step is complete when the Vertex settings and indicator combination produce the most favorable results. Step 9. Go to Section 4 and enable “Apply Red Base To Base Margin”. Step 10. Go to Section 5 and enable “Apply Blue Base To Base Margin”. Step 11. Go to Section 2 and adjust “Minimum Base To Base Blue” and “Minimum Base To Base Red”. Observe the chart and note where the markers move relative to each other. Markers further apart will produce less trades but will reduce cutoffs in “Ping Pong” mode. Step 12. Turn off Show Markers in Section 2. Step 13. Put in your Minimum Profit and Stop Loss in the first section. This is in pips or currency basis points (chart right side scale). Percentage is not currently supported. Note that the profit is taken as a conditional exit on a market order not a fixed limit. The actual profit taken will almost always be greater than the amount specified. The stop loss, on the other hand, is indeed a hard number which is executed by the TradingView broker simulator when the threshold is breached. Step 14. Return to step 3 and select a Trading Mode (Long, Short, BiDir, Ping Pong). If you are planning to trade bidirectionally its best to configure long first then short. Combine them with “BiDir” or “Ping Pong” after setting up both sides of the trade individually. The difference between “BiDir” and “Ping Pong” is that “Ping Pong” uses position reversal and can cut off opposing trades less than the specified minimum profit. As a result “Ping Pong” mode produces the greatest number of trades. Step 15. Take a look at the chart. Trades should be showing along the markers plotted earlier. Step 16. Make adjustments to the Vertex fields in Section 2 until the TradingView performance report is showing a profit. This includes the “Minimum Base To Base” fields. If a profit cannot be achieved move on to Step 17. Step 17. Improve the backtest profitability by adjusting the “Entry Net Change” and “Entry ROC” in Section 4 and 5. Step 18. Enable the “Mandatory Snap” checkbox in Section 4 and 5 and adjust the “Snap Candle Delta” and “Snap Fractal Delta” in Section 2. This should reduce some chop producing unprofitable reversals. Step 19. Increase the distance between opposing trades by adding an “Interleave Delta” in Sections 4 and 5. This is a floating point value which starts at 0.01 and typically does not exceed 2.0. Step 20. Increase the distance between opposing trades even further by adding a “Decay Minimum Span” in Sections 4 and 5. This is an absolute value specified in the symbol’s quote currency (right side scale of the chart). This value is similar to the minimum profit and stop loss fields in Section 1. Step 21. The “Buy Composite Strength” input works in tandem with “Long Decay Minimum Span” in Section 4. Try enabling and see if it improves the performance. This field is only relevant when there is a value in “Long Decay Minimum Span”. Step 22. The “Sell Composite Weakness” input works in tandem with “Short Decay Minimum Span” in Section 5. Try enabling and see if it improves the performance. This field is only relevant when there is a value in “Short Decay Minimum Span”. Step 23. Improve the backtest profitability by adjusting the “Adherence Delta” in Section 4 and 5. This field requires the “Adhere to Rising Trend” checkbox to be enabled. Step 24. At this point your strategy should be more or less working. Experiment with the remaining check boxes in Section 4 and 5. Keep the ones which seem to improve the performance. Step 25. Examine the chart and see that trades are being placed in accordance with your desired trading goals. This is an important step. If your desired model requires multiple trades per day then you should be seeing hundreds of trades on the chart. Alternatively, you may be looking to trade fewer steep peaks and deep valleys in which case you should see trades at major turning points. Don’t simply settle for what the backtest serves you. Work your configuration until the system aligns with your desired model. Try changing indicators and even intervals if you cannot reach your simulation goals. Generally speaking, the histogram and Candle indicators produce the most trades. The Fractal indicator captures the tallest peaks and valleys. The Transform indicator is the most reliable but doesn’t well work on all instruments. Example Settings To reproduce the performance shown on the chart please use the following configuration: 1. Select XBTUSD Kraken as the chart symbol. 2. On the properties tab set the Order Size to: 0.01 Bitcoin 3. On the properties tab set the Pyramiding to: 10 4. In Section 1: Select “Forex” for the Instrument Type 5. In Section 1: Select “Ping Pong” for the Trading Mode 6. In Section 1: Input 1200 for the Minimum Profit 7. In Section 1: Input 15000 for the Stop Offset 8. In Section 1: Input 1200 for the Pyramid Minimum Span 9. In Section 1: Check mark the Ultra Wide Pyramids 10. In Section 2: Check mark the Use Transform Indicator So to be clear, I used a base position size of one - one hundredth of a Bitcoin and allow the script to add up to 10 downward pyramids. The example back-test did hit eight downward pyramids. That means the account would have to be able to withstand a base position size (0.01) times 28. The resulting position size is 0.28 of a Bitcoin. If the price of Bitcoin is 35K then the draw down amount (not including broker fees) would be $9800 dollars. Since I have a premium subscription my backtest chart includes 20K historical bars. That's roughly six months of data. As of today, pro accounts only get 10K bars so the performance cannot be exactly matched with such a difference in historical data. Please keep that in mind. There are, of course, various ways to reduce the risk incurred from accumulating pyramids. You can increase the “Pyramid Minimum Span” input found in Section 2 which increases the space between each pyramid trade. Also you can set a “Pyramid Bale Out Offset” in the same input section. This lets you out of the trade faster on position recovery. For example: Set a value of 8000 into this input and the number of trades increase to 178 from 157. Since the positions didn’t go full term, more trades were created at less profit each. The total brute force approach would be to simply limit the number of pyramids in the Properties tab. It should be noted that since this is crypto, accumulating on the long side may be what you want. If you are not trading on margin and thus outright buying coins on the Kraken exchange you likely are interested in increasing your Bitcoin position at depressed prices. This is a popular feature on some of the other crypto trading packages like CryptoHopper and Profit Trailer. Click on Enable TV Long Only Rule in Section 1. This switches the signal emitter to long only. However, you may still see short trades on the chart. They are treated as a close instead of a reversal. Feel free to PM me with any questions related to this script. Thank you and happy trading! CFTC RULE 4.41 These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.

Strategi Pine Script®

oleh tradingtudi

Telah dikemas kini

Range Oscillator Strategy + Stoch Confirm 🔹 Short summary This is a free, educational long-only strategy built on top of the public “Range Oscillator” by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. It’s a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades. ──────────────────────── 0. Legal / risk disclaimer ──────────────────────── • This script is FREE and public. I do not charge any fee for it. • It is for EDUCATIONAL PURPOSES ONLY. • It is NOT financial advice and does NOT guarantee profits. • Backtest results can be very different from live results. • Markets change over time; past performance is NOT indicative of future performance. • You are fully responsible for your own trades and risk. Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital. ──────────────────────── 1. About default settings and risk (very important) ──────────────────────── The script is configured with the following defaults in the `strategy()` declaration: • `initial_capital = 10000` → This is only an EXAMPLE account size. • `default_qty_type = strategy.percent_of_equity` • `default_qty_value = 100` → This means 100% of equity per trade in the default properties. → This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade. TradingView’s House Rules recommend risking only a small part of equity per trade (often 1–2%, max 5–10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to: 1. Open **Strategy Settings → Properties**. 2. Set: • Order size: **Percent of equity** • Order size (percent): e.g. **1–2%** per trade 3. Make sure **commission** and **slippage** match your own broker conditions. • By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets. If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading. ──────────────────────── 2. What this strategy tries to do (conceptual overview) ──────────────────────── This is a LONG-ONLY strategy designed to explore the combination of: 1. **Range Oscillator (Zeiierman-based)** - Measures how far price has moved away from an adaptive mean. - Uses an ATR-based range to normalize deviation. - High positive oscillator values indicate strong price expansion away from the mean in a bullish direction. 2. **Stochastic as a timing filter** - A classic Stochastic (%K and %D) is used. - The logic requires %K to be below a user-defined level and then crossing above %D. - This is intended to catch moments when momentum turns up again, rather than chasing every extreme. 3. **EMA Exit Filter (trend slope)** - An EMA with configurable length (default 70) is calculated. - The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition. - This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted. 4. **Optional risk-management layer** - Percentage-based Stop Loss and Take Profit (SL/TP). - Risk/Reward (R-multiple) exit based on the distance from entry to SL. - Implemented as OCO orders that work *on top* of the logical exits. The goal is not to create a “holy grail” system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes. ──────────────────────── 3. Components and how they work together ──────────────────────── (1) Range Oscillator (based on “Range Oscillator (Zeiierman)”) • The script computes a weighted mean price and then measures how far price deviates from that mean. • Deviation is normalized by an ATR-based range and expressed as an oscillator. • When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction. • When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled). (2) Stochastic confirmation • Classic Stochastic (%K and %D) is calculated. • An entry requires: - %K to be below a user-defined “Cross Level”, and - then %K to cross above %D. • This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point. (3) EMA Exit Filter • The EMA length is configurable via `emaLength` (default 70). • The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA. • If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition. • This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit. (4) Risk management (optional) • Stop Loss (SL) and Take Profit (TP): - Defined as percentages relative to average entry price. - Both are disabled by default, but you can enable them in the Inputs. • Risk/Reward Exit: - Uses the distance from entry to SL to project a profit target at a configurable R-multiple. - Also optional and disabled by default. These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first. ──────────────────────── 4. Entry & Exit logic (high level) ──────────────────────── A) Time filter • You can choose a **Start Year** in the Inputs. • Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`). • This prevents accidental use of tiny cherry-picked windows and makes tests more honest. B) Entry condition (long-only) A long entry is allowed when ALL the following are true: 1. `timeCondition` is true (inside the backtest window). 2. If `useOscEntry` is true: - Range Oscillator value must be above `entryLevel`. 3. If `useStochEntry` is true: - Stochastic condition (`stochCondition`) must be true: - %K < `crossLevel`, then %K crosses above %D. If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`. C) Exit condition (logical exits) A position can be closed when: 1. `timeCondition` is true AND a long position is open, AND 2. At least one of the following is true: - If `useOscExit` is true: Oscillator is below `exitLevel`. - If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`). In that case, `strategy.close("Long")` is called. D) Risk-management exits While a position is open: • If SL or TP is enabled: - `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages. • If Risk/Reward exit is enabled: - `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance. These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels. ──────────────────────── 5. Recommended backtest configuration (to avoid misleading results) ──────────────────────── To align with TradingView House Rules and avoid misleading backtests: 1. **Initial capital** - 10 000 (or any value you personally want to work with). 2. **Order size** - Type: **Percent of equity** - Size: **1–2%** per trade is a reasonable starting point. - Avoid risking more than 5–10% per trade if you want results that could be sustainable in practice. 3. **Commission & slippage** - Commission: around 0.1% if that matches your broker. - Slippage: a few ticks (e.g. 3) to account for real fills. 4. **Timeframe & markets** - Volatile symbols (e.g. crypto like BTCUSDT, or major indices). - Timeframes: 1H / 4H / **1D (Daily)** are typical starting points. - I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes. 5. **No “caution warning”** - Make sure your chosen symbol + timeframe + settings do not trigger TradingView’s caution messages. - If you see warnings (e.g. “too few trades”), adjust timeframe/symbol or the backtest period. ──────────────────────── 5a. About low trade count and rare signals ──────────────────────── This strategy is intentionally designed to trade RARELY: • It is **long-only**. • It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter). • On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest. TradingView’s House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case: • The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window. • The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals. • Because of the low trade count, results should NOT be interpreted as statistically strong or “proven” – they are only one sample of how this logic would have behaved on past data. Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample. ──────────────────────── 6. How to use this strategy (step-by-step) ──────────────────────── 1. Add the script to your chart. 2. Open the **Inputs** tab: - Set the backtest start year. - Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter. - Optionally enable SL, TP, and Risk/Reward exits. 3. Open the **Properties** tab: - Set a realistic account size if you want. - Set order size to a realistic % of equity (e.g. 1–2%). - Confirm that commission and slippage are realistic for your broker. 4. Run the backtest: - Look at Net Profit, Max Drawdown, number of trades, and equity curve. - Remember that a low trade count means the statistics are not very strong. 5. Experiment: - Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params. - See how the metrics and trade frequency change. 6. Forward-test: - Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time. ──────────────────────── 7. Originality and usefulness (why this is more than a mashup) ──────────────────────── This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component: • Range Oscillator: - Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric. • Stochastic: - Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn. • EMA Exit Filter: - Trend-slope-based safety net to exit when the medium-term direction changes against the position. • Risk module: - Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic. It aims to give traders a ready-made **framework to study and modify**, not a black box or “signals” product. ──────────────────────── 8. Limitations and good practices ──────────────────────── • No single strategy works on all markets or in all regimes. • This script is long-only; it does not short the market. • Performance can degrade when market structure changes. • Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit. Good practices: - Test on multiple symbols and timeframes. - Focus on stability and drawdown, not only on how high the profit line goes. - View this as a learning tool and a basis for your own research. ──────────────────────── 9. Licensing and credits ──────────────────────── • Core oscillator idea & base code: - “Range Oscillator (Zeiierman)” - © Zeiierman, licensed under CC BY-NC-SA 4.0. • Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer: - Modifications by jokiniemi. Please respect both the original license and TradingView House Rules if you fork or republish any part of this script. ──────────────────────── 10. No payments / no vendor pitch ──────────────────────── • This script is completely FREE to use on TradingView. • There is no paid subscription, no external payment link, and no private signals group attached to it. • If you have questions, please use TradingView’s comment system or private messages instead of expecting financial advice. Use this script as a tool to learn, experiment, and build your own understanding of markets. ──────────────────────── 11. Example backtest settings used in screenshots ──────────────────────── To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration: • Symbol: BTCUSDT (or similar major BTC pair) • Timeframe: 1D (Daily) • Backtest period: from 2018 to the most recent data • Initial capital: 10 000 • Order size type: Percent of equity • Order size: 2% per trade • Commission: 0.1% • Slippage: 3 ticks • Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default • Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.

Strategi Pine Script®

PHANTOM STRIKE Z-4 [ApexLegion]Phantom Strike Z-4 STRATEGY OVERVIEW This strategy represents an analytical framework using 6 detection systems that analyze distinct market dimensions through adaptive timeframe optimization. Each system targets specific market inefficiencies - automated parameter adjustment, market condition filtering, phantom strike pattern detection, SR exit management, order block identification, and volatility-aware risk management - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions. SYSTEM ARCHITECTURE PHILOSOPHY Phantom Strike Z-4 operates through 12 distinct parameter groups encompassing individual settings that allow detailed customization for different trading environments. The strategy employs modular design principles where each analytical component functions independently while contributing to unified decision-making protocols. This architecture enables traders to engage with structured market analysis through intuitive configuration options while the underlying algorithms handle complex computational processes. The framework approaches certain aspects differently from static trading approaches by implementing real-time parameter adjustment based on timeframe characteristics, market volatility conditions, news event detection, and weekend gap analysis. During low-volatility periods where traditional strategies struggle to generate meaningful returns, Z-4's adaptive systems identify micro-opportunities through formation analysis and systematic patience protocols. 🔍WHY THESE CUSTOM SYSTEMS WERE INDEPENDENTLY DEVELOPED The strategy approaches certain aspects differently from traditional indicator combinations through systematic development of original analytical approaches: # 1. Auto Timeframe Optimization Module (ATOM) Problem Identification: Standard strategies use fixed parameters regardless of timeframe characteristics, leading to over-optimization on specific timeframes and reduced effectiveness when market conditions change between different time intervals. Most retail traders manually adjust parameters when switching timeframes, creating inconsistency and suboptimal results. Traditional approaches may not account for how market noise, signal frequency, and intended holding periods differ substantially between 1-minute scalping and 4-hour swing trading environments. Custom Solution Development: The ATOM system addresses these limitations through systematic parameter matrices developed specifically for each timeframe environment. During development, analysis indicated that 1-minute charts require aggressive profit-taking approaches due to rapid price reversals, while 15-minute charts benefit from patient position holding during trend development. The system automatically detects chart timeframe through TradingView's built-in functions and applies predefined parameter configurations without user intervention. Timeframe-Specific Adaptations: For ultra-short timeframe trading (1-minute charts), the system recognizes that market noise dominates price action, requiring tight stop losses (1.0%) and rapid profit realization (25% at TP1, 35% at TP2, 40% at TP3). Position sizes automatically reduce to 3% of equity to accommodate the higher trading frequency while mission duration limits to 20 bars prevent extended exposure during unsuitable conditions. Medium timeframe configurations (5-minute and 15-minute charts) balance signal quality with execution frequency. The 15-minute configuration aims to provide a favorable combination of signal characteristics and practical execution for most retail traders. Formation thresholds increase to 2.0% for both stealth and strike ready levels, requiring stronger momentum confirmation before signal activation. Longer timeframe adaptations (1-hour and 4-hour charts) accommodate swing trading approaches where positions may develop over multiple trading sessions. Position sizing increases to 10% of equity reflecting the reduced signal frequency and higher validation requirements typical of swing trading. Take profit targets extend considerably (TP1: 2.0%, TP2: 4.0%, TP3: 8.0%) to capture larger price movements characteristic of these timeframes. # 2. Market Condition Filtering System (MCFS) Problem Identification: Existing volatility filters use simple ATR calculations that may not distinguish between trending volatility and chaotic noise, potentially affecting signal quality during news events, market transitions, and unusual trading sessions. Traditional volatility measurements treat all price movement equally, whether it represents genuine trend development or random market noise caused by low liquidity or algorithmic trading activities. Custom Solution Architecture: The MCFS addresses these limitations through multi-dimensional market analysis that examines volatility characteristics, external market influences, and temporal factors affecting trading conditions. Rather than relying solely on price-based volatility measurements, the system incorporates news event detection, weekend gap analysis, and session transition monitoring to provide systematic market state assessment. Volatility Classification and Response Framework: • EXTREME Volatility Conditions (>2.5x average ATR): When current volatility exceeds 250% of the recent average, the system recognizes potentially chaotic market conditions that often occur during major news events, market crashes, or significant fundamental developments. During these periods, position sizing automatically reduces by 70% while exit sensitivity increases by 50%. • HIGH Volatility Conditions (1.8-2.5x average ATR): High volatility environments often represent strong trending conditions or elevated market activity that still maintains some predictability. Position sizing reduces by 40% while maintaining standard signal generation processes. • NORMAL Volatility Conditions (1.2-1.8x average ATR): Normal volatility represents favorable trading conditions where technical analysis may provide reliable signals and market behavior tends to follow predictable patterns. All strategy parameters operate at standard settings. • LOW Volatility Conditions (0.8-1.2x average ATR): Low volatility environments may present opportunities for increased position sizing due to reduced risk and improved signal characteristics. Position sizing increases by 30% while profit targets extend to capture larger movements when they occur. • DEAD Volatility Conditions (<0.8x average ATR): When volatility falls below 80% of recent averages, the system suspends trading activity to avoid choppy, directionless market conditions that may produce unfavorable risk-adjusted returns. # 3. Phantom Strike Detection Engine (PSDE) Problem Identification: Traditional momentum indicators may lag market reversals by 2-4 bars and can generate signals during consolidation periods. Existing oscillator combinations may lack precision in identifying high-probability momentum shifts with adequate filtering mechanisms. Most trading systems rely on single-indicator signals or simple two-indicator confirmations that may not distinguish between genuine momentum changes and temporary market fluctuations. Multi-Indicator Convergence System: The PSDE addresses these limitations through structured multi-indicator convergence requiring simultaneous confirmation across four independent momentum systems: SuperTrend directional analysis, MACD histogram acceleration, Parabolic SAR momentum validation, and CCI buffer zone detection. This approach recognizes that each indicator provides unique market insights, and their convergence may create different trading opportunity characteristics compared to individual signals. Enhanced vs Phantom Mode Operation: Enhanced mode activates when at least three of the four primary indicators align with directional bias while meeting minimum validation criteria. Enhanced mode provides more frequent signals while Phantom mode offers more selective signal generation with stricter confirmation requirements. Phantom mode requires complete alignment across all four indicators plus additional momentum validation. All Enhanced mode criteria must be met, plus additional confirmation requirements. This stricter requirement set reduces signal frequency to 5-8 monthly but aims for higher signal quality through comprehensive multi-indicator alignment and additional momentum validation. # 4. Smart Resistance Exit Grid (SR Exit Grid) Problem Identification: Static take-profit levels may not account for changing market conditions and momentum strength. Traditional trailing stops may exit during strong moves or during reversals, while not distinguishing between profitable and losing position characteristics. Systematic Holding Evaluation Framework: The SR Exit Grid operates through continuous evaluation of position viability rather than predetermined price targets through a structured 4-stage priority hierarchy: 🎯 1st Priority: Standard Take Profit processing (Highest Priority) 🔄 2nd Priority: SMART EXIT (Only when TP not executed) ⛔ 3rd Priority: SL/Emergency/Timeout Exit 🛡️ 4th Priority: Smart Low Logic (Separate Safety Safeguard) The system employs a tpExecuted flag mechanism ensuring that only one exit type activates per bar, preventing conflicting orders and maintaining execution priority. Each stage operates independently with specific trigger conditions and risk management protocols. Fast danger scoring evaluates immediate threats including SAR distance deterioration, momentum reversals, extreme CCI readings, volatility spikes, and price action intensity. When combined scores exceed specified thresholds (8.0+ danger with <2.0 confidence), the system triggers protective exits regardless of current profitability. # 5. Order Block Tracking System (OBTS) Problem Identification: Standard support/resistance levels are static and may not account for institutional order flow patterns. Traditional approaches may use horizontal lines without considering market structure evolution or mathematical price relationships. Dynamic Channel Projection Logic: The OBTS creates dynamic order block identification using pivot point analysis with parallel channel projection based on mathematical price geometry. The system identifies significant turning points through configurable swing length parameters while maintaining historical context through consecutive pivot tracking for trend analysis. Rather than drawing static horizontal lines, the system calculates slope relationships between consecutive pivot points and projects future support/resistance levels based on mathematical progression. This approach recognizes that institutional order flow may follow geometric patterns that can be mathematically modeled and projected forward. # 6. Volatility-Aware Risk Management (VARM) Problem Identification: Fixed percentage risk management may not adapt optimally during varying market volatility regimes, potentially creating conservative exits in low volatility and limited protection during high volatility periods. Traditional approaches may not scale dynamically with market conditions. Dual-Mode Adaptive Framework: The VARM provides systematic risk scaling through dual-mode architecture offering both ATR-based dynamic adjustment and fixed percentage modes. Dynamic mode automatically scales all TP/SL levels based on current market volatility while maintaining proportional risk-reward relationships. Fixed mode provides predictable percentage-based levels regardless of volatility conditions. Emergency protection protocols operate independently from standard risk management, providing enhanced safeguards against significant moves that exceed normal volatility expectations. The emergency system cannot be disabled and triggers at wider levels than normal stops, providing final protection when standard risk management may be insufficient during extreme market events. ## Technical Formation Analysis System The foundation of Z-4's analytical framework rests on a structured EMA system utilizing 8, 21, and 50-period exponential moving averages that create formation structure analysis. This system differs from simple crossover signals by evaluating market geometry and momentum alignment. Formation Gap Analysis: The formation gap measurement calculates the percentage separation between Recon Scout EMA (8-period) and Technical Support EMA (21-period) to determine market state classification. When gap percentage falls below the Stealth Mode Threshold (default 1.5%), the market enters consolidation phase requiring enhanced patience. When gap exceeds Strike Ready Threshold (1.5%), conditions become favorable for momentum-based entries. This mathematical approach to formation analysis provides structured measurement of market transition states. During stealth mode periods, the strategy reduces entry frequency while maintaining monitoring protocols. Strike ready conditions activate increased signal sensitivity and quicker entry evaluation processes. The Command Base EMA (50-period) provides strategic context for overall market direction and trend strength measurement. Position decisions incorporate not only immediate formation geometry but also alignment with longer-term directional bias represented by Command Base positioning relative to current price action. 🎯CORE SYSTEMS TECHNICAL IMPLEMENTATION # SuperTrend Foundation Analysis Implementation SuperTrend calculation provides the directional foundation through volatility-adjusted bands that adapt to current market conditions rather than using fixed parameters. The system employs configurable ATR length (default 10) and multiplier (default 3.0) to create dynamic support/resistance levels that respond to both trending and ranging market environments. Volatility-Adjusted Band Calculation: st_atr = ta.atr(stal) st_hl2 = (high + low) / 2 st_ub = st_hl2 + stm * st_atr st_lb = st_hl2 - stm * st_atr stb = close > st and ta.rising(st, 3) The HL2 methodology (high+low)/2 aims to provide stable price reference compared to closing prices alone, reducing sensitivity to intraday price spikes that can distort traditional SuperTrend calculations. ATR multiplication creates bands that expand during volatile periods and contract during consolidation, aiming for suitable signal sensitivity across different market conditions. Rising/Falling Trend Confirmation: The key feature involves requiring rising/falling trend confirmation over multiple periods rather than simple price-above-band validation. This requirement screens signals that occur during SuperTrend whipsaw periods common in sideways markets. SuperTrend signals with 3-period rising confirmation help reduce false signals that occur during sideways market conditions compared to simple crossover signals. Band Distance Validation: The system measures the distance between current price and SuperTrend level as a percentage of current price, requiring minimum separation thresholds to identify meaningful momentum rather than marginal directional changes. This validation aims to reduce signal generation during periods where price oscillates closely around SuperTrend levels, indicating indecision rather than clear directional bias. # MACD Histogram Acceleration System - Momentum Detection MACD analysis focuses exclusively on histogram acceleration rather than traditional line crossovers, aiming to provide earlier momentum detection. This approach recognizes that histogram acceleration may precede price acceleration by 1-2 bars, potentially offering timing benefits compared to conventional MACD applications. Acceleration-Based Signal Generation: mf = ta.ema(close, mfl) ms = ta.ema(close, msl) ml = mf - ms msg = ta.ema(ml, msgl) mh = ml - msg mb = mh > 0 and mh > mh and mh > mh The requirement for positive histogram values that increase over two consecutive periods aims to identify genuine momentum expansion rather than temporary fluctuations. This filtering approach aims to reduce false signals while maintaining signal quality. Fast/Slow EMA Optimization: The default 12/26 EMA combination aims for intended balance between responsiveness and stability for most trading timeframes. However, the system allows customization for specific market characteristics or trading styles. Shorter settings (8/21) increase sensitivity for scalping approaches, while longer settings (16/32) provide smoother signals for swing trading applications. Signal Line Smoothing Effects: The 9-period signal line smoothing creates histogram values that screen high-frequency noise while preserving essential momentum information. This smoothing level aims to balance signal latency and accuracy across multiple market conditions. # Parabolic SAR Validation Framework - Momentum Verification Parabolic SAR provides momentum validation through price separation analysis and inflection detection that may precede significant trend changes. The system requires minimum separation thresholds while monitoring SAR behavior for early reversal signals. Separation-Based Validation: sar = ta.sar(ss, si, sm) sarb = close > sar and (close - sar) / close > 0.005 sardp = math.abs(close - sar) / close * 100 sariu = sarm > 0 and sarm < 0 and math.abs(sarmc) > saris The 0.5% minimum separation requirement screens marginal directional changes that may reverse within 1-3 bars. The 0.5% minimum separation requirement helps filter out marginal directional changes. SAR Inflection Detection: SAR inflection identification examines rate-of-change over 5-period lookback periods to detect momentum direction changes before they appear in price action. Inflection sensitivity (default 1.5) determines the magnitude of momentum change required for classification. These inflection points may precede significant price reversals by 1-2 bars, potentially providing early signals for position protection or entry timing. Strength Classification Framework: The system categorizes SAR momentum into weak/moderate/strong classifications based on distance percentage relative to strength range thresholds. Strong momentum periods (>75% of range) receive enhanced weighting in composite calculations, while weak periods (<25%) trigger additional confirmation requirements. This classification aims to distinguish between genuine momentum moves and temporary price fluctuations. # CCI SMART Buffer Zone System - Oscillator Analysis The CCI SMART system represents a detailed component of the PSDE, combining multiple mathematical techniques to create modified momentum detection compared to conventional CCI applications. The system employs ALMA preprocessing, TANH normalization, and dynamic buffer zone analysis for market timing. ALMA Preprocessing Benefits: Arnaud Legoux Moving Average preprocessing aims to provide phase-neutral smoothing that reduces high-frequency noise while preserving essential momentum information. The configurable offset (0.85) and sigma (6.0) parameters create Gaussian filter characteristics that aim to maintain signal timing while reducing unwanted signals caused by random price fluctuations. TANH Normalization Advantages: The rational TANH approximation creates bounded output (-100 to +100) that aims to prevent extreme readings from distorting analysis while maintaining sensitivity to normal market conditions. This normalization is designed to provide consistent behavior across different volatility regimes and market conditions, addressing an aspect found in traditional CCI applications. Rational TANH Approximation Implementation: rational_tanh(x) => abs_x = math.abs(x) if abs_x >= 4.0 x >= 0 ? 1.0 : -1.0 else x2 = x * x numerator = x * (135135 + x2 * (17325 + x2 * (378 + x2))) denominator = 135135 + x2 * (62370 + x2 * (3150 + x2 * 28)) numerator / denominator cci_smart = rational_tanh(cci / 150) * 100 The rational approximation uses polynomial coefficients that provide mathematical precision equivalent to native TANH functions while maintaining computational efficiency. The 4.0 absolute value threshold creates complete saturation at extreme values, while the polynomial series delivers smooth S-curve transformation for intermediate values. Dynamic Buffer Zone Analysis: Unlike static support/resistance levels, the CCI buffer system creates zones that adapt to current market volatility through ALMA-calculated true range measurements. Upper and lower boundaries expand during volatile periods and contract during consolidation, providing context-appropriate entry and exit levels. CCI Buffer System Implementation: cci = ta.cci(close, ccil) cci_atr = ta.alma(ta.tr, al, ao, asig) cci_bu = low - ccim * cci_atr cci_bd = high + ccim * cci_atr ccitu = cci > 50 and cci > cci CCI buffer analysis creates dynamic support/resistance zones using ALMA-smoothed true range calculations rather than fixed levels. Buffer upper and lower boundaries adapt to current market volatility through ALMA calculation with configurable offset (default 0.85) and sigma (default 6.0) parameters. The CCI trending requirements (>50 and rising) provide directional confirmation while buffer zone analysis offers price level validation. This dual-component approach identifies both momentum direction and suitable entry/exit price levels relative to current market volatility. # Momentum Gathering and Assessment Framework The strategy incorporates a dual-component momentum system combining RSI and MFI calculations into unified momentum assessment with configurable suppression and elevation thresholds. Composite Momentum Calculation: ri = ta.rsi(close, mgp) mi = ta.mfi(close, mip) ci = (ri + mi) / 2 us = ci < sl // Undersupported conditions ed = ci > dl // Elevated conditions The composite momentum score averages RSI and MFI over configurable periods (default 14) to create unified momentum measurement that incorporates both price momentum and volume-weighted momentum. This dual-factor approach provides different momentum assessment compared to single-indicator analysis. Suppression level identification (default 35) indicates oversold conditions where counter-trend opportunities may develop. These conditions often coincide with formation analysis showing bullish progression potential, creating enhanced-validation long entry scenarios. Elevation level detection (default 65) identifies overbought conditions suitable for either short entries or long position exits depending on overall market context. The momentum assessment operates continuously, providing real-time context for all entry and exit decisions. Rather than using fixed thresholds, the system evaluates momentum levels relative to formation geometry and volatility conditions to determine suitable response protocols. Composite Signal Generation Architecture: The strategy employs a systematic scoring framework that aggregates signals from independent analytical modules into unified decision matrices through mathematical validation protocols rather than simple indicator combinations. Multi-Group Signal Analysis Structure: The scoring architecture operates through three analytical timeframe groups, each targeting different market characteristics and response requirements: ✅Fast Group Analysis (Immediate Response): Fast group scoring evaluates immediate market conditions requiring rapid assessment and response. SAR distance analysis measures price separation from parabolic SAR as percentage of close price, with distance ratios exceeding 120% of strength range indicating momentum exhaustion (3.0 points). SAR momentum detection captures rate-of-change over 5-period lookback, with absolute momentum exceeding 2.0% indicating notable acceleration or deceleration (1.0 point). ✅Medium Group Analysis (Signal Development): Medium group scoring focuses on signal development and confirmation through momentum indicator progression. Phantom Strike detection operates in two modes: Enhanced mode requiring 4-component confirmation awards 3.0 base points, while Phantom mode requiring complete alignment plus additional criteria awards 4.0 base points. ✅Slow Group Analysis (Strategic Context): Slow group analysis provides strategic market context through trend regime classification and structural assessment. Trend classification scoring awards top points (3.5) for optimal conditions: major trend bullish with strong trend strength (>2.0% EMA spread), 2.8 points for normal strength major trends, and proportional scoring for various trend states. Signal Integration and Quality Assessment: The integration process combines medium group tactical scoring with 30% weighting from slow group strategic assessment, recognizing that immediate signal development should receive primary emphasis while strategic context provides important validation. Fast group danger levels operate as filtering mechanisms rather than additive scoring components. Score normalization converts raw calculations to 10-point scales through division by total possible score (19.6) and multiplication by 10. This standardization enables consistent threshold application regardless of underlying calculation complexity while maintaining proportional relationships between different signal strength levels. Conflict Resolution and Priority Logic: sc = math.abs(cs_les - cs_ses) < 1.5 hqls = sql and not sc and (cs_les > cs_ses * 1.15) hqss = sqs and not sc and (cs_ses > cs_les * 1.15) Signal conflict detection identifies situations where competing long/short signals occur simultaneously within 1.5-point differential. During conflict periods, the system requires 15% threshold margin plus absence of conflict conditions for signal activation, screening trades during uncertain market conditions. 🧠CONFIGURATION SETTINGS & USAGE GUIDE Understanding Parameter Categories and Their Impact The Phantom Strike Z-4 strategy organizes its numerous parameters into 12 logical groups, each controlling specific aspects of market analysis and position management. Understanding these parameter relationships enables users to customize the strategy for different trading styles, market conditions, and risk preferences without compromising the underlying analytical framework. Parameter Group Overview and Interaction: Parameters within the strategy do not operate in isolation. Changes to formation thresholds affect signal generation frequency, which in turn impacts intended position sizing and risk management settings. Similarly, timeframe optimization automatically adjusts multiple parameter groups simultaneously, creating coordinated system behavior rather than piecemeal modifications. Safe Modification Ranges: Each parameter includes minimum and maximum values that prevent system instability or illogical configurations. These ranges are designed to maintain strategy behavior stability and functional operation. Operating outside these ranges may result in either excessive conservatism (missed opportunities) or excessive aggression (increased risk without proportional reward). # Tactical Formation Parameters (Group 1) - Foundation Configuration **EMA Period Settings and Market Response** Recon Scout EMA (Default: 8 periods): The fastest moving average in the system, providing immediate price action response and early momentum detection. This parameter influences signal sensitivity and entry timing characteristics. Values between 5-12 periods may work across most market conditions, with specific adjustment based on trading style and timeframe preferences. -Conservative Setting (10-12 periods): Reduces signal frequency by approximately 25% while potentially improving accuracy by 8-12%. Suitable for traders preferring fewer, higher-quality signals with reduced monitoring requirements. -Standard Setting (8 periods): Provides balanced performance with moderate signal frequency and reasonable accuracy. Represents intended configuration for most users based on backtesting across multiple market conditions. -Aggressive Setting (5-6 periods): Increases signal frequency by 35-40% while accepting 5-8% accuracy reduction. Appropriate for active traders comfortable with increased position monitoring and faster decision-making requirements. Technical Support EMA (Default: 21 periods): Creates medium-term trend reference and formation gap calculations that determine market state classification. This parameter establishes the baseline for consolidation detection and momentum confirmation, influencing the strategy's approach to distinguish between trending and ranging market conditions. Command Base EMA (Default: 50 periods): Provides strategic context and long-term trend classification that influences overall market bias and position sizing decisions. This slower moving average acts as a filter for trade direction, helping support alignment with broader market trends rather than counter-trend trading against major market movements. **Formation Threshold Configuration** Stealth Mode Threshold (Default: 1.5%): Defines the maximum percentage gap between Recon Scout and Technical Support EMAs that indicates market consolidation. When the gap falls below this threshold, the market enters "stealth mode" requiring enhanced patience and reduced entry frequency. This parameter influences how the strategy behaves during sideways market conditions. -Tight Threshold (0.8-1.2%): Creates more restrictive consolidation detection, reducing entry frequency during marginal trending conditions but potentially improving accuracy by avoiding low-momentum signals. -Standard Threshold (1.5%): Provides balanced consolidation detection suitable for most market conditions and trading styles. -Loose Threshold (2.0-3.0%): Permits trading during moderate consolidation periods, increasing opportunity capture but accepting some reduction in signal quality during transitional market phases. -Strike Ready Threshold (Default: 1.5%): Establishes minimum EMA separation required for momentum-based entries. When the gap exceeds this threshold, conditions become favorable for signal generation and position entry. This parameter works inversely to Stealth Mode, determining when market conditions support active trading. # Momentum System Configuration (Group 2) - Momentum Assessment **Oscillator Period Settings** Momentum Gathering Period (Default: 14): Controls RSI calculation length, influencing momentum detection sensitivity and signal timing. This parameter determines how quickly the momentum system responds to price momentum changes versus how stable the momentum readings remain during normal market fluctuations. -Fast Response (7-10 periods): Aims for rapid momentum detection suitable for scalping approaches but may generate more unwanted signals during choppy market conditions. -Standard Response (14 periods): Provides balanced momentum measurement appropriate for most trading styles and timeframes. -Smooth Response (18-25 periods): Creates more stable momentum readings suitable for swing trading but with delayed response to momentum changes. -Mission Indicator Period (Default: 14): Determines MFI (Money Flow Index) calculation length, incorporating volume-weighted momentum analysis alongside price-based RSI measurements. The relationship between RSI and MFI periods affects how the composite momentum score behaves during different market conditions. **Momentum Threshold Configuration** -Suppression Level (Default: 35): Identifies oversold conditions indicating potential bullish reversal opportunities. This threshold determines when the momentum system signals that selling pressure may be exhausted and buying interest could emerge. Lower values create more restrictive oversold identification, while higher values increase sensitivity to potential reversal conditions. -Dominance Level (Default: 65): Establishes overbought thresholds for potential bearish reversals or long position exit consideration. The separation between Suppression and Dominance levels creates a neutral zone where momentum conditions don't strongly favor either direction. # Phantom Strike System Configuration (Group 3) - Core Signal Generation **System Activation and Mode Selection** Phantom Strike System Enable (Default: True): Activates the core signal generation methodology combining SuperTrend, MACD, SAR, and CCI confirmation requirements. Disabling this system converts the strategy to basic formation analysis without advanced momentum confirmation, substantially affecting signal characteristics while increasing frequency. Phantom Strike Mode (Default: PHANTOM): Determines signal generation strictness through different confirmation requirements. This setting fundamentally affects trading frequency, signal accuracy, and required monitoring intensity. ENHANCED Mode: Requires 4-component confirmation with moderate validation criteria. Suitable for active trading approaches where signal frequency balances with accuracy requirements. PHANTOM Mode: Requires complete alignment across all indicators plus additional momentum criteria. Appropriate for selective trading approaches where signal quality takes priority over frequency. **SuperTrend Configuration** SuperTrend ATR Length (Default: 10): Determines volatility measurement period for dynamic band calculation. This parameter affects how quickly SuperTrend bands adapt to changing market conditions and how sensitive the trend detection becomes to short-term price movements. SuperTrend Multiplier (Default: 3.0): Controls band width relative to ATR measurements, influencing trend change sensitivity and signal frequency. This parameter determines how much price movement is required to trigger trend direction changes. **MACD System Parameters** MACD Fast Length (Default: 12): Establishes responsive EMA for MACD line calculation, influencing histogram acceleration detection timing and signal sensitivity. MACD Slow Length (Default: 26): Creates baseline EMA for MACD calculations, establishing the reference for momentum measurement. MACD Signal Length (Default: 9): Smooths MACD line to generate histogram values used for acceleration detection. **Parabolic SAR Settings** SAR Start (Default: 0.02): Determines initial acceleration factor affecting early SAR behavior after trend initiation. SAR Increment (Default: 0.02): Controls acceleration factor increases as trends develop, affecting how quickly SAR approaches price during sustained moves. SAR Maximum (Default: 0.2): Establishes upper limit for acceleration factor, preventing rapid SAR approach speed during extended trends. **CCI Buffer System Configuration** CCI Length (Default: 20): Determines period for CCI calculation, affecting oscillator sensitivity and signal timing. CCI ATR Length (Default: 5): Controls period for ALMA-smoothed true range calculations used in dynamic buffer zone creation. CCI Multiplier (Default: 1.0): Determines buffer zone width relative to ATR calculations, affecting entry requirements and signal frequency. ⭐HOW TO USE THE STRATEGY # Step 1: Core Parameter Setup Technical Formation Group (g1) - Foundation Settings: The Technical Formation group provides the foundational analytical framework through 7 key parameters that influence signal generation and timeframe optimization. Auto Optimization Controls: enable_auto_tf = input.bool(false, "🎯 Enable Auto Timeframe Optimization") enable_market_filters = input.bool(true, "🌪️ Enable Market Condition Filters") Auto Timeframe Optimization activation automatically detects chart timeframe and applies configured parameter matrices developed for each time interval. When enabled, the system overrides manual settings with backtested suggested values for 1M/5M/15M/1H configurations. Market Condition Filters enable real-time parameter adjustment based on volatility classification, news event detection, and weekend gap analysis. This system provides adaptive behavior during unusual market conditions, automatically reducing position sizes during extreme volatility and increasing exit sensitivity during news events. # Step 2: The Momentum System Configuration Momentum Gathering Parameters (g2): The Momentum System combines RSI and MFI calculations into unified momentum assessment with configurable thresholds for market state classification. # Step 3: Phantom Strike System Setup Core Detection Parameters (g3): The Phantom Strike System represents the strategy's primary signal generation engine through multi-indicator convergence analysis requiring detailed configuration for intended performance. Phantom Strike Mode selection determines signal generation strictness. Enhanced mode requires 4-component confirmation (SuperTrend + MACD + SAR + CCI) with base scoring of 3.0 points, structured for active trading with moderate confirmation requirements. Phantom mode requires complete alignment across all indicators plus additional momentum criteria with 4.0 base scoring, creating enhanced validation signals for selective trading approaches # Step 4: SR Exit Grid Configuration Position Management Framework (g6): The SR Exit Grid system manages position lifecycle through progressive profit-taking and adaptive holding evaluation based on market condition analysis. esr = input.bool(true, "Enable SR Exit Grid") ept = input.bool(true, "Enable Partial Take Profit") ets = input.bool(true, "Enable Technical Trailing Stop") 📊MULTI-TIMEFRAME SYSTEM & ADAPTIVE FEATURES Auto Timeframe Optimization Architecture: The Auto Timeframe Optimization system provides automated parameter adaptation that automatically configures strategy behavior based on chart timeframe characteristics with reduced need for manual adjustment. 1-Minute Ultra Scalping Configuration: get_1M_params() => StrategyParams.new( smt = 0.8, srt = 1.0, mcb = 2, mmd = 20, smartThreshold = 0.1, consecutiveLimit = 20, positionSize = 3.0, enableQuickEntry = true, ptp1 = 25, ptp2 = 35, ptp3 = 40, tm1 = 1.5, tm2 = 3.0, tm3 = 4.5, tmf = 6.0, isl = 1.0, esl = 2.0, tsd = 0.5, dsm = 1.5) 15-Minute Swing Trading Configuration: get_15M_params() => StrategyParams.new( smt = 2.0, srt = 2.0, mcb = 8, mmd = 100, smartThreshold = 0.3, consecutiveLimit = 12, positionSize = 7.0, enableQuickEntry = false, ptp1 = 15, ptp2 = 25, ptp3 = 35, tm1 = 4.0, tm2 = 8.0, tm3 = 12.0, tmf = 18.0, isl = 2.0, esl = 3.5, tsd = 1.2, dsm = 2.5) Market Condition Filter Integration: if enable_market_filters vol_condition = get_volatility_condition() is_news = is_news_time() is_gap = is_weekend_gap() step1 = adjust_for_volatility(base_params, vol_condition) step2 = adjust_for_news(step1, is_news) final_params = adjust_for_gap(step2, is_gap) Market condition filters operate in conjunction with timeframe optimization to provide systematic parameter adaptation based on both temporal and market state characteristics. The system applies cascading adjustments where each filter modifies parameters before subsequent filter application. Volatility Classification Thresholds: - EXTREME: >2.5x average ATR (70% position reduction, 50% exit sensitivity increase) - HIGH: 1.8-2.5x average (40% position reduction, increased monitoring) - NORMAL: 1.2-1.8x average (standard operations) - LOW: 0.8-1.2x average (30% position increase, extended targets) - DEAD: <0.8x average (trading suspension) The volatility classification system compares current 14-period ATR against a 50-period moving average to establish baseline market activity levels. This approach aims to provide stable volatility assessment compared to simple ATR readings, which can be distorted by single large price movements or temporary market disruptions. 🖥️TACTICAL HUD INTERPRETATION GUIDE Overview of the 21-Component Real-Time Information System The Tactical HUD Display represents the strategy's systematic information center, providing real-time analysis through 21 distinct data points organized into 6 logical categories. This system converts complex market analysis into actionable insights, enabling traders to make informed decisions based on systematic market assessment supporting informed decision-making processes. The HUD activates through the "Show Tactical HUD" parameter and displays continuously in the top-right corner during live trading and backtesting sessions. The organized 3-column layout presents Item, Value, and Status for each component, creating efficient information density while maintaining clear readability under varying market conditions. # Row 1: Mission Status - Advanced Position State Management Display Format: "LONG MISSION" | "SHORT MISSION" | "STANDBY" Color Coding: Green (Long Active) | Red (Short Active) | Gray (Standby) Status Indicator: ✓ (Mission Active) | ○ (No Position) "LONG MISSION" Active State Management: Long mission status indicates the strategy currently maintains a bullish position with all systematic monitoring systems engaged in active position management mode. During this important state, the system regularly evaluates holding scores through multi-component analysis, monitors TP progression across all three target levels, tracks Smart Exit criteria through fast danger and confidence assessment, and adjusts risk management parameters based on evolving position development and changing market conditions. "SHORT MISSION" Position Management: Short mission status reflects active bearish position management with systematic monitoring systems engaged in structured defensive protocols designed for the unique characteristics of bearish market movements. The system operates in modified inverse mode compared to long positions, monitoring for systematic downward TP progression while maintaining protective exit criteria specifically calibrated for bearish position development patterns. "STANDBY" Strategic Market Scanning Mode: Standby mode indicates no active position exposure with all systematic analytical systems operating in scanning mode, regularly evaluating evolving market conditions for qualified entry opportunities that meet the strategy's confirmation requirements. # Row 2: Auto Timeframe | Market Filters - System Configuration Display Format: "1M ULTRA | ON" | "5M SCALP | OFF" | "MANUAL | ON" Color Coding: Lime (Auto Optimization Active) | Gray (Manual Configuration) Timeframe-Specific Configuration Indicators: • 1M ULTRA: One-minute ultra-scalping configuration configured for rapid-fire trading with accelerated profit capture (25%/35%/40% TP distribution), conservative risk management (3% position sizing, 1.0% initial stops), and increased Smart Exit sensitivity (0.1 threshold, 20-bar consecutive limit). • 15M SWING: Fifteen-minute swing trading configuration representing the strategy's intended performance environment, featuring conservative TP distribution (15%/25%/35%), expanded position sizing (7% allocation), extended target multipliers (4.0/8.0/12.0/18.0 ATR). • MANUAL: User-defined parameter configuration without automatic adjustment, requiring manual modification when switching timeframes but providing full customization control for experienced traders. Market Filter Status: ON: Real-time volatility classification and market condition adjustments modifying strategy behavior through automated parameter scaling. OFF: Standard parameter operation only without dynamic market condition adjustments. # Row 3: Signal Mode - Sensitivity Configuration Framework Display Format: "BALANCED" | "AGGRESSIVE" Color Coding: Aqua (Balanced Mode) | Red (Aggressive Mode) "BALANCED" Mode Characteristics: Balanced mode utilizes structured conservative signal sensitivity requiring enhanced verification across all analytical components before allowing signal generation. This rigorous configuration requires Medium Group scoring ≥5.5 points, Slow Group confirmation ≥3.5 points, and Fast Danger levels ≤2.0 points. "AGGRESSIVE" Mode Characteristics: Aggressive mode strategically reduces confirmation requirements to increase signal frequency while accepting moderate accuracy reduction. Threshold requirements decrease to Medium Group ≥4.5 points, Slow Group ≥2.5 points, and Fast Danger ≤1.0 points. # Row 4: PS Mode (Phantom Strike Mode) - Core Signal Generation Engine Display Format: "ENHANCED" | "PHANTOM" | "DISABLED" Color Coding: Aqua (Enhanced Mode) | Lime (Phantom Mode) | Gray (Disabled) "ENHANCED" Mode Operation: Enhanced mode operates the structured 4-component confirmation system (SuperTrend directional analysis + MACD histogram acceleration + Parabolic SAR momentum validation + CCI buffer zone confirmation) with systematically configured moderate validation criteria, awarding 3.0 base points for signal strength calculation. "PHANTOM" Mode Operation: Phantom mode utilizes enhanced verification requirements supporting complete alignment across all analytical indicators plus additional momentum validation criteria, awarding 4.0 base points for signal strength calculation within the selective performance framework. # Row 5: PS Confirms (Phantom Strike Confirmations) - Real-Time Signal Development Tracking Display Format: "ST✓ MACD✓ SAR✓ CCI✓" | Individual component status display Color Coding: White (Component Status Text) | Dynamic Count Color (Green/Yellow/Red) Individual Component Interpretation: • ST✓ (SuperTrend Confirmation): SuperTrend confirmation indicates established bullish directional alignment with current price positioned above calculated SuperTrend level plus rising trend validation over the required confirmation period. • MACD✓ (Histogram Acceleration Confirmation): MACD confirmation requires positive histogram values demonstrating clear acceleration over the specified confirmation period. • SAR✓ (Momentum Validation Confirmation): SAR confirmation requires bullish directional alignment with minimum price separation requirements to identify meaningful momentum rather than marginal directional change. • CCI✓ (Buffer Zone Confirmation): CCI confirmation requires trending conditions above 50 midline with momentum continuation, indicating that oscillator conditions support established directional bias. # Row 6: Mission ROI - Performance Measurement Including All Costs Display Format: "+X.XX%" | "-X.XX%" | "0.00%" Color Coding: Green (Positive Performance) | Red (Negative Performance) | Gray (Breakeven) Real ROI provides position performance measurement including detailed commission cost analysis (0.15% round-trip transaction costs), representing actual profitability rather than theoretical gains that ignore trading expenses. # Row 7: Exit Grid + Remaining Position - Progressive Target Management Display Format: "TP3 ✓ (X% Left)" | "TP2 ✓ (X% Left)" | "TP1 ✓ (X% Left)" | "TRACKING (X% Left)" | "STANDBY (100%)" Color Coding: Green (TP3 Achievement) | Yellow (TP2 Achievement) | Orange (TP1 Achievement) | Aqua (Active Tracking) | Gray (No Position) • TP1 Achievement Analysis: TP1 achievement represents initial profit capture with 20% of original position closed at first target level, supporting signal quality assessment while maintaining 80% position exposure for continued profit potential. • TP2 Achievement Analysis: TP2 achievement indicates meaningful profit realization with cumulative 50% position closure, suggesting favorable signal development while maintaining meaningful 50% exposure for potential extended profit scenarios. • TP3 Achievement Analysis: TP3 achievement represents notable position performance with 90% cumulative closure, suggesting favorable signal development and effective market timing. # Row 8: Entry Signal - Signal Strength Assessment and Readiness Analysis Display Format: "LONG READY (X.X/10)" | "SHORT READY (X.X/10)" | "WAITING (X.X/10)" Color Coding: Lime (Long Signal Ready) | Red (Short Signal Ready) | Gray (Insufficient Signal) Signal Strength Classification: • High Signal Strength (8.0-10.0/10): High signal strength indicates market conditions with systematic analytical alignment supporting directional bias through confirmation across all evaluation criteria. These conditions represent optimal entry scenarios with strong analytical support. • Strong Signal Quality (6.0-7.9/10): Strong signal quality represents solid market conditions with analytical alignment supporting directional thesis through systematic confirmation protocols. These signals meet enhanced validation requirements for quality entry opportunities. • Moderate Signal Strength (4.5-5.9/10): Moderate signal strength indicates basic market conditions meeting minimum entry requirements through systematic confirmation satisfaction. # Row 9: Major Trend Analysis - Strategic Direction Assessment Display Format: "X.X% STRONG BULL" | "X.X% BULL" | "X.X% BEAR" | "X.X% STRONG BEAR" | "NEUTRAL" Color Coding: Lime (Strong Bull) | Green (Bull) | Red (Bear) | Dark Red (Strong Bear) | Gray (Neutral) • Strong Bull Conditions (>3.0% with Bullish Structure): Strong bull classification indicates substantial upward trend strength with EMA spread exceeding 3.0% combined with favorable bullish structure alignment. These conditions represent strong momentum environments where trend persistence may show notable probability characteristics. • Standard Bull Conditions (1.5-3.0% with Bullish Structure): Standard bull classification represents healthy upward trend conditions with moderate momentum characteristics supporting continued bullish bias through systematic structural analysis. # Row 10: EMA Formation Analysis - Structural Assessment Framework Display Format: "BULLISH ADVANCE" | "BEARISH RETREAT" | "NEUTRAL" Color Coding: Lime (Strong Bullish) | Red (Strong Bearish) | Gray (Neutral/Mixed) • BULLISH ADVANCE Formation Analysis: Bullish Advance indicates systematic positive EMA alignment with upward structural development supporting sustained directional momentum. This formation represents favorable conditions for bullish position strategies through mathematical validation of structural strength and momentum persistence characteristics. • BEARISH RETREAT Formation Analysis: Bearish Retreat indicates systematic negative EMA alignment with downward structural development supporting continued bearish momentum through mathematical validation of structural deterioration patterns. # Row 11: Momentum Status - Composite Momentum Oscillator Assessment Display Format: "XX.X | STATUS" (Composite Momentum Score with Assessment) Color Coding: White (Score Display) | Assessment-Dependent Status Color The Momentum Status system combines Relative Strength Index (RSI) and Money Flow Index (MFI) calculations into unified momentum assessment providing both price-based and volume-weighted momentum analysis. • SUPPRESSED Conditions (<35 Momentum Score): SUPPRESSED classification indicates oversold market conditions where selling pressure may be reaching exhaustion levels, potentially creating favorable conditions for bullish reversal opportunities. • ELEVATED Conditions (>65 Momentum Score): ELEVATED classification indicates overbought market conditions where buying pressure may be reaching unsustainable levels, creating potential bearish reversal scenarios. # Row 12: CCI Information Display - Momentum Direction Analysis Display Format: "XX.X | UP" | "XX.X | DOWN" Color Coding: Lime (Bullish Momentum Trend) | Red (Bearish Momentum Trend) The CCI Information Display showcases the CCI SMART system incorporating Arnaud Legoux Moving Average (ALMA) preprocessing combined with rational approximation of the hyperbolic tangent (TANH) function to achieve modified signal processing compared to traditional CCI implementations. CCI Value Interpretation: • Extreme Bullish Territory (>80): CCI readings exceeding +80 indicate extreme bullish momentum conditions with potential overbought characteristics requiring careful evaluation for continued position holding versus profit-taking consideration. • Strong Bullish Territory (50-80): CCI readings between +50 and +80 indicate strong bullish momentum with favorable conditions for continued bullish positioning and standard target expectations. • Neutral Momentum Zone (-50 to +50): CCI readings within neutral territory indicate ranging momentum conditions without strong directional bias, suitable for patient signal development monitoring. • Strong Bearish Territory (-80 to -50): CCI readings between -50 and -80 indicate strong bearish momentum creating favorable conditions for bearish positioning while suggesting caution for bullish strategies. • Extreme Bearish Territory (<-80): CCI readings below -80 indicate extreme bearish momentum with potential oversold characteristics creating possible reversal opportunities when combined with supportive analytical factors. # Row 13: SAR Network - Multi-Component Momentum Analysis Display Format: "X.XX% | BULL STRONG ↗INF" | Complex Multi-Component Analysis Color Coding: Lime (Bullish Strong) | Green (Bullish Moderate) | Red (Bearish Strong) | Orange (Bearish Moderate) | White (Inflection Priority) SAR Distance Percentage Analysis: The distance percentage component measures price separation from SAR level as percentage of current price, providing quantification of momentum strength through mathematical price relationship analysis. SAR Strength Classification Framework: • STRONG Momentum Conditions (>75% of Strength Range): STRONG classification indicates significant momentum conditions with price-SAR separation exceeding 75% of calculated strength range, representing notable directional movement with sustainability characteristics. • MODERATE Momentum Conditions (25-75% of Range): MODERATE classification represents normal momentum development with suitable directional characteristics for standard positioning strategies and normal target expectations. • WEAK Momentum Conditions (<25% of Range): WEAK classification indicates minimal momentum with price-SAR separation below 25% of strength range, suggesting potential reversal zones or ranging conditions unsuitable for strong directional strategies. Inflection Detection System: • Bullish Inflection (↗INF): Bullish inflection detection identifies moments when SAR momentum transitions from declining to rising through systematic rate-of-change analysis over 5-period lookback periods. These inflection points may precede significant bullish price reversals by 1-2 bars. • Bearish Inflection (↘INF): Bearish inflection detection captures SAR momentum transitions from rising to declining, indicating potential bearish reversal development benefiting from prompt attention for position management evaluation. # Row 14: VWAP Context Analysis - Institutional Volume-Weighted Price Reference Display Format: "Daily: XXXX.XX (+X.XX%)" | "N/A (Index/Futures)" Color Coding: Lime (Above VWAP Premium) | Red (Below VWAP Discount) | Gray (Data Unavailable) Volume-Weighted Average Price (VWAP) provides institutional-level price reference showing mathematical average price where significant volume has transacted throughout the specified period. This calculation represents fair value assessment from institutional perspective. • Above VWAP Conditions (✓ Status - Lime Color): Price positioning above VWAP indicates current market trading at premium to volume-weighted average, suggesting buyer willingness to pay above fair value for continued position accumulation. • Below VWAP Conditions (✗ Status - Red Color): Price positioning below VWAP indicates current market trading at discount to volume-weighted average, creating potential value opportunities for accumulation while suggesting seller pressure exceeding buyer demand at fair value levels. # Row 15: TP SL System Configuration - Dynamic vs Static Target Management Display Format: "DYNAMIC ATR" | "STATIC %" Color Coding: Aqua (Dynamic ATR Mode) | Yellow (Static Percentage Mode) • DYNAMIC ATR Mode Analysis: Dynamic ATR mode implements systematic volatility-adaptive target management where all profit targets and stop losses automatically scale based on current market volatility through ATR (Average True Range) calculations. This approach aims to keep target levels proportionate to actual market movement characteristics rather than fixed percentages that may become unsuitable during changing volatility regimes. • STATIC % Mode Analysis: Static percentage mode implements traditional fixed percentage targets (default 1.0%/2.5%/3.8%/4.5%) regardless of current market volatility conditions, providing predictable target levels suitable for traders preferring fixed percentage objectives without volatility-based adjustments. # Row 16: TP Sequence Progression - Systematic Achievement Tracking Display Format: "1 ✓ 2 ✓ 3 ○" | "1 ○ 2 ○ 3 ○" | Progressive Achievement Display Color Coding: White text with systematic achievement progression Status Indicator: ✓ (Achievement Confirmed) | ○ (Target Not Achieved) • Complete Achievement Sequence (1 ✓ 2 ✓ 3 ✓): Complete sequence achievement represents significant position performance with systematic profit realization across all primary target levels, indicating favorable signal quality and effective market timing. • Partial Achievement Analysis: Partial achievement patterns provide insight into position development characteristics and market condition assessment. TP1 achievement suggests signal timing effectiveness while subsequent target achievement depends on continued momentum development. • No Achievement Display (1 ○ 2 ○ 3 ○): No achievement indication represents early position development phase or challenging market conditions requiring patience for target realization. # Row 17: Mission Duration Tracking - Time-Based Position Management Display Format: "XX/XXX" (Current Bars/Maximum Duration Limit) Color Coding: Green (<50% Duration) | Orange (50-80% Duration) | Red (>80% Duration) • Normal Duration Periods (Green Status <50%): Normal duration indicates position development within expected timeframes based on signal characteristics and market conditions, representing healthy position progression without time pressure concerns. • Extended Duration Periods (Orange Status 50-80%): Extended duration indicates position development requiring longer timeframes than typical expectations, warranting increased monitoring for resolution through either target achievement or protective exit consideration. • Critical Duration Periods (Red Status >80%): Critical duration approaches maximum holding period limits, requiring immediate resolution evaluation through either target achievement acceleration, Smart Exit activation, or systematic timeout protocols. # Row 18: Last Exit Analysis - Historical Exit Pattern Assessment Display Format: Exit Reason with Color-Coded Classification Color Coding: Lime (TP Exits) | Red (Critical Exits) | Yellow (Stop Losses) | Purple (Smart Low) | Orange (Timeout/Sustained) • Profit-Taking Exits (Lime/Green): TP1/TP2/TP3/Final Target exits indicate position management with systematic profit realization suggesting signal quality and strategy performance. • Critical/Emergency Exits (Red): Critical and Emergency exits indicate protective system activation during adverse market conditions, showing risk management through early threat detection and systematic protective response. • Smart Low Exits (Purple): Smart Low exits represent behavioral finance safeguards activating at -3.5% ROI threshold when emotional trading patterns may develop, aiming to reduce emotional decision-making during extended negative performance periods. # Row 19: Fast Danger Assessment - Immediate Threat Detection System Display Format: "X.X/10" (Danger Score out of 10) Color Coding: Green (<3.0 Safe) | Yellow (3.0-5.0 Moderate) | Red (>5.0 High Danger) The Fast Danger Assessment system provides real-time evaluation of immediate market threats through six independent measurement systems: SAR distance deterioration, momentum reversal detection, extreme CCI readings, volatility spike analysis, price action intensity, and combined threat evaluation. • Safe Conditions (Green <3.0): Safe danger levels indicate stable market conditions with minimal immediate threats to position viability, enabling position holding with standard monitoring protocols. • Moderate Concern (Yellow 3.0-5.0): Moderate danger levels indicate developing threats requiring increased monitoring and preparation for potential protective action, while not immediately demanding position closure. • High Danger (Red >5.0): High danger levels indicate significant immediate threats requiring immediate protective evaluation and potential position closure consideration regardless of current profitability. # Row 20: Holding Confidence Evaluation - Position Viability Assessment Display Format: "X.X/10" (Confidence Score out of 10) Color Coding: Green (>6.0 High Confidence) | Yellow (3.0-6.0 Moderate Confidence) | Red (<3.0 Low Confidence) Holding Confidence evaluation provides systematic assessment of position viability through analysis of trend strength maintenance, formation quality persistence, momentum sustainability, and overall market condition favorability for continued position development. • High Confidence (Green >6.0): High confidence indicates strong position viability with supporting factors across multiple analytical dimensions, suggesting continued position holding with extended target expectations and reduced exit sensitivity. • Moderate Confidence (Yellow 3.0-6.0): Moderate confidence indicates suitable position viability with mixed supporting factors requiring standard position management protocols and normal exit sensitivity. • Low Confidence (Red <3.0): Low confidence indicates deteriorating position viability with weakening supporting factors across multiple analytical dimensions, requiring increased protective evaluation and potential Smart Exit activation. # Row 21: Volatility | Market Status - Volatility Environment & Market Filter Status Display Format: "NORMAL | NORMAL" | "HIGH | HIGH VOL" | "EXTREME | NEWS FILTER" Color Coding: White (Information display) Volatility Classification Component (Left Side): - DEAD: ATR ratio <0.8x average, minimal price movement requiring careful timing - LOW: ATR ratio 0.8-1.2x average, stable conditions enabling position increase potential - NORMAL: ATR ratio 1.2-1.8x average, typical market behavior with standard parameters - HIGH: ATR ratio 1.8-2.5x average, elevated movement requiring increased caution - EXTREME: ATR ratio >2.5x average, chaotic conditions triggering enhanced protection Market Status Component (Right Side): - NORMAL: Standard market conditions, no special filters active - HIGH VOL: High volatility detected, position reduction and exit sensitivity increased - EXTREME VOL: Extreme volatility confirmed, enhanced protective protocols engaged - NEWS FILTER: Major economic event detected, 80% position reduction active - GAP MODE: Weekend gap identified, increased caution until normal flow resumes Combined Status Interpretation: - NORMAL | NORMAL: Suitable trading conditions, standard strategy operation - HIGH | HIGH VOL: Elevated volatility confirmed by both systems, 40% position reduction - EXTREME | EXTREME VOL: High volatility warning, 70% position reduction active 📊VISUAL SYSTEM INTEGRATION Chart Analysis & Market Visualization CCI SMART Buffer Zone Visualization System - Dynamic Support/Resistance Framework Dynamic Zone Architecture: The CCI SMART buffer system represents systematic visual integration creating adaptive support and resistance zones that automatically expand and contract based on current market volatility through ALMA-smoothed true range calculations. These dynamic zones provide real-time support and resistance levels that adapt to evolving market conditions rather than static horizontal lines that quickly become obsolete. Adaptive Color Intensity Algorithm: The buffer visualization employs color intensity algorithms where transparency and saturation automatically adjust based on CCI momentum strength and directional persistence. Stronger momentum conditions produce more opaque visual representations with increased saturation, while weaker momentum creates subtle transparency indicating reduced prominence or significance. Color Interpretation Framework for Strategic Decision Making: -Intense Blue/Purple (High Opacity): Strong CCI readings exceeding ±80 with notable momentum strength indicating support/resistance zones suitable for increased position management decisions • Moderate Blue/Purple (Medium Opacity): Standard CCI readings ranging ±40-80 with normal momentum indicating support/resistance areas for standard position management protocols • Faded Blue/Purple (High Transparency): Weak CCI readings below ±40 with minimal momentum suggesting cautious interpretation and conservative position management approaches • Dynamic Color Transitions: Automatic real-time shifts between bullish (blue spectrum) and bearish (purple spectrum) based on CCI trend direction and momentum persistence characteristics CCI Inflection Circle System - Momentum Reversal Identification: The inflection detection system creates distinctive visual alerts through dual-circle design combining solid cores with transparent glow effects for enhanced visibility across different chart backgrounds and timeframe configurations. Inflection Circle Classification: • Neon Green Circles: CCI extreme bullish inflection detected (>80 threshold) with systematic core + glow effect indicating bearish reversal warning for position management evaluation • Hot Pink Circles: CCI extreme bearish inflection detected (<-80 threshold) with dual-layer visualization indicating bullish reversal opportunity for strategic entry consideration • Dual-Circle Design Architecture: Solid tiny core providing location identification with large transparent glow ensuring visibility without chart obstruction across multiple timeframe analyses SAR Visual Network - Multi-Layer Momentum Display Architecture SAR Visualization Framework: The SAR visual system implements structured multi-layer display architecture incorporating trend lines, strength classification markers, and momentum analysis through various visual elements that automatically adapt to current momentum conditions and strength characteristics. SAR Strength Visual Classification System: • Bright Triangles (High Intensity): Strong SAR momentum exceeding 75% of calculated strength range, indicating significant momentum quality suitable for increased positioning considerations and extended target scenarios • Standard Circles (Medium Intensity): Moderate SAR momentum within 25-75% strength range, representing normal momentum development appropriate for standard positioning approaches and regular target expectations • Faded Markers (Low Intensity): Weak SAR momentum below 25% strength range, suggesting caution and conservative positioning during minimal momentum conditions with increased exit sensitivity ⚠️IMPORTANT DISCLAIMERS AND RISK WARNINGS Past Performance Limitations: The backtesting results presented represent hypothetical performance based on historical market data and do not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice. No trading strategy can guarantee 100% success or eliminate the risk of loss. Users must approach trading with appropriate caution, never risking more than they can afford to lose. Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.

Strategi Pine Script®

oleh ApexLegion

AlgoBuilder [Trend-Following] | Fractalyst What's the strategy's purpose and functionality? This strategy is designed for both traders and investors looking to rely on and trade based on historical and backtested data using automation. The main goal is to build profitable trend-following strategies that outperform the underlying asset in terms of returns while minimizing drawdown. For example, as for a benchmark, if the S&P 500 (SPX) has achieved an estimated 10% annual return with a maximum drawdown of -57% over the past 20 years, using this strategy with different entry and exit techniques, users can potentially seek ways to achieve a higher Compound Annual Growth Rate (CAGR) while maintaining a lower maximum drawdown. Although the strategy can be applied to all markets and timeframes, it is most effective on stocks, indices, future markets, cryptocurrencies, and commodities and JPY currency pairs given their trending behaviors. In trending market conditions, the strategy employs a combination of moving averages and diverse entry models to identify and capitalize on upward market movements. It integrates market structure-based trailing stop-loss mechanisms across different timeframes and provides exit techniques, including percentage-based and risk-reward (RR) based take profit levels. Additionally, the strategy has also a feature that includes a built-in probability and sentiment function for traders who want to implement probabilities and market sentiment right into their trading strategies. Performance summary, weekly, and monthly tables enable quick visualization of performance metrics like net profit, maximum drawdown, compound annual growth rate (CAGR), profit factor, average trade, average risk-reward ratio (RR), and more. This aids optimization to meet specific goals and risk tolerance levels effectively. ----- How does the strategy perform for both investors and traders? The strategy has two main modes, tailored for different market participants: Traders and Investors. Trading: 1. Trading (1x): - Designed for traders looking to capitalize on bullish trending markets. - Utilizes a percentage risk per trade to manage risk and optimize returns. - Suitable for active trading with a focus on trend-following and risk management. - (1x) This mode ensures no stacking of positions, allowing for only one running position or trade at a time. ◓: Mode | %: Risk percentage per trade 2. Trading (2x): Similar to the 1x mode but allows for two pyramiding entries. This approach enables traders to increase their position size as the trade moves in their favor, potentially enhancing profits during strong bullish trends. ◓: Mode | %: Risk percentage per trade 3. Investing: - Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown. - Utilizes 100% of the equity to buy, hold, and manage the asset. - Focuses on long-term growth and capital appreciation by fully investing in the asset during bullish conditions. - ◓: Mode | %: Risk not applied (In investing mode, the strategy uses 100% of equity to buy the asset) ----- What's the purpose of using moving averages in this strategy? What are the underlying calculations? Using moving averages is a widely-used technique to trade with the trend. The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages. The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns. By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades. The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition. This comparison filter can be turned on (>/<) or off. For example, you can set the filter so that MA#1 > MA#2, meaning the first moving average must be above the second one before the script looks for entry conditions. This adds an extra layer of trend confirmation, ensuring that trades are only taken in more favorable market conditions. MA #1: Fast MA | MA #2: Medium MA | MA #3: Slow MA ⍺: MA Period | Σ: MA Timeframe ----- What entry modes are used in this strategy? What are the underlying calculations? The strategy by default uses two different techniques for the entry criteria with user-adjustable left and right bars: Breakout and Fractal. 1. Breakout Entries : - The strategy looks for pivot high points with a default period of 3. - It stores the most recent high level in a variable. - When the price crosses above this most recent level, the strategy checks if all conditions are met and the bar is closed before taking the buy entry. ◧: Pivot high left bars period | ◨: Pivot high right bars period 2. Fractal Entries : - The strategy looks for pivot low points with a default period of 3. - When a pivot low is detected, the strategy checks if all conditions are met and the bar is closed before taking the buy entry. ◧: Pivot low left bars period | ◨: Pivot low right bars period By utilizing these entry modes, the strategy aims to capitalize on bullish price movements while ensuring that the necessary conditions are met to validate the entry points. ----- What type of stop-loss identification method are used in this strategy? What are the underlying calculations? Initial Stop-Loss: 1. ATR Based: The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves. Calculation: - To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close. The True Range is the largest of the following: - Current Period High minus Current Period Low - Absolute Value of Current Period High minus Previous Period Close - Absolute Value of Current Period Low minus Previous Period Close - The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14). Example - ATR (14) * 1.5 ⍺: ATR period | Σ: ATR Multiplier 2. ADR Based: The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days. Calculation: - To calculate the ADR for a particular day: - Calculate the average of the high prices over a specified number of days. - Calculate the average of the low prices over the same number of days. - Find the difference between these average values. - The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements. Example - ADR (14) * 1.5 ⍺: ADR period | Σ: ADR Multiplier Application in Strategy: - The strategy calculates the current bar's ADR/ATR with a user-defined period. - It then multiplies the ADR/ATR by a user-defined multiplier to determine the initial stop-loss level. By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. Trailing Stop-Loss: One of the key elements of this strategy is its ability to detec buyside and sellside liquidity levels across multiple timeframes to trail the stop-loss once the trade is in running profits. By utilizing this approach, the strategy allows enough room for price to run. There are two built-in trailing stop-loss (SL) options you can choose from while in a trade: 1. External Trailing Stop-Loss: - Uses sell-side liquidity to trail your stop-loss, allowing price to consolidate before continuation. This method is less aggressive and provides more room for price fluctuations. Example - External - Wick below the trailing SL - 12H trailing timeframe ⍺: Exit type | Σ: Trailing stop-loss timeframe 2. Internal Trailing Stop-Loss: - Uses the most recent swing low with a period of 2 to trail your stop-loss. This method is more aggressive compared to the external trailing stop-loss, as it tightens the stop-loss closer to the current price action. Example - Internal - Close below the trailing SL - 6H trailing timeframe ⍺: Exit type | Σ: Trailing stop-loss timeframe Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. ----- What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations? For Break-Even: - You can choose to set a break-even level at which your initial stop-loss moves to the entry price as soon as it hits, and your trailing stop-loss gets activated (if enabled). - You can select either a percentage (%) or risk-to-reward (RR) based break-even, allowing you to set your break-even level as a percentage amount above the entry price or based on RR. For TP1 (Take Profit 1): - You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled. - Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR. For TP2 (Take Profit 2): - You can choose to set a take profit level at which your position gets fully closed. - As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR. The underlying calculations involve determining the price levels at which these actions are triggered. For break-even, it moves the initial stop-loss to the entry price and activate the trailing stop-loss once the break-even level is reached. For TP1 and TP2, it's specifying the price levels at which the position is partially or fully closed based on the chosen method (percentage or RR) above the entry price. These calculations are crucial for managing risk and optimizing profitability in the strategy. ⍺: BE/TP type (%/RR) | Σ: how many RR/% above the current price ----- What's the ADR filter? What does it do? What are the underlying calculations? The Average Day Range (ADR) measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days. The period of the ADR filter used in this strategy is tied to the same period you've used for your initial stop-loss. Users can define the minimum ADR they want to be met before the script looks for entry conditions. ADR Bias Filter: - Compares the current bar ADR with the ADR (Defined by user): - If the current ADR is higher, it indicates that volatility has increased compared to ADR (DbU).(⬆) - If the current ADR is lower, it indicates that volatility has decreased compared to ADR (DbU).(⬇) Calculations: 1. Calculate ADR: - Average the high prices over the specified period. - Average the low prices over the same period. - Find the difference between these average values in %. 2. Current ADR vs. ADR (DbU): - Calculate the ADR for the current bar. - Calculate the ADR (DbU). - Compare the two values to determine if volatility has increased or decreased. By using the ADR filter, the strategy ensures that trades are only taken in favorable market conditions where volatility meets the user's defined threshold, thus optimizing entry conditions and potentially improving the overall performance of the strategy. >: Minimum required ADR for entry | %: Current ADR comparison to ADR of 14 days ago. ----- What's the probability filter? What are the underlying calculations? The probability filter is designed to enhance trade entries by using buyside liquidity and probability analysis to filter out unfavorable conditions. This filter helps in identifying optimal entry points where the likelihood of a profitable trade is higher. Calculations: 1. Understanding Swing highs and Swing Lows Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right. Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right. 2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels. 3. Understanding probability calculations 1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive 2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active 3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences. 5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities. Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity. Example - BSL > 50% ----- What's the sentiment Filter? What are the underlying calculations? Sentiment filter aims to calculate the percentage level of bullish or bearish fluctuations within equally divided price sections, in the latest price range. Calculations: This filter calculates the current sentiment by identifying the highest swing high and the lowest swing low, then evenly dividing the distance between them into percentage amounts. If the price is above the 50% mark, it indicates bullishness, whereas if it's below 50%, it suggests bearishness. Sentiment Bias Identification: Bullish Bias: The current price is trading above the 50% daily range. Bearish Bias: The current price is trading below the 50% daily range. Example - Sentiment Enabled | Bullish degree above 50% | Bullish sentimental bias >: Minimum required sentiment for entry | %: Current sentimental degree in a (Bullish/Bearish) sentimental bias ----- What's the range length Filter? What are the underlying calculations? The range length filter identifies the price distance between buyside and sellside liquidity levels in percentage terms. When enabled, the script only looks for entries when the minimum range length is met. This helps ensure that trades are taken in markets with sufficient price movement. Calculations: Range Length (%) = ( ( Buyside Level − Sellside Level ) / Current Price ) ×100 Range Bias Identification: Bullish Bias: The current range price has broken above the previous external swing high. Bearish Bias: The current range price has broken below the previous external swing low. Example - Range length filter is enabled | Range must be above 5% | Price must be in a bearish range >: Minimum required range length for entry | %: Current range length percentage in a (Bullish/Bearish) range ----- What's the day filter Filter, what does it do? The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style. Customize Session Time: Users can define the start and end times for the trading session. This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours. Select Days: Users can select which days of the week to include in the strategy. This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays). Benefits: Focus on Optimal Trading Periods: By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities. Avoid Unfavorable Conditions: Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays. Increased Flexibility: The filter provides increased flexibility, allowing traders to adapt the strategy to their specific needs and preferences. Example - Day filter | Session Filter θ: Session time | Exchange time-zone ----- What tables are available in this script? Table Type: - Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades, Compound Annual Growth Rate (CAGR), MAR and more. CAGR: It calculates the 'Compound Annual Growth Rate' first and last taken trades on your chart. The CAGR is a notional, annualized growth rate that assumes all profits are reinvested. It only takes into account the prices of the two end points — not drawdowns, so it does not calculate risk. It can be used as a yardstick to compare the performance of two strategies. Since it annualizes values, it requires a minimum 4H timeframe to display the CAGR value. annualizing returns over smaller periods of times doesn't produce very meaningful figures. MAR: Measure of return adjusted for risk: CAGR divided by Max Drawdown. Indicates how comfortable the system might be to trade. Higher than 0.5 is ideal, 1.0 and above is very good, and anything above 3.0 should be considered suspicious and you need to make sure the total number of trades are high enough by running a Deep Backtest in strategy tester. (available for TradingView Premium users.) Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit. MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position. Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses. Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit. Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most trend-following successful strategies have a percent profitability of 15-40% but are profitable due to risk management control. BE Trades: Number of break-even trades, excluding commission/slippage. Losing Trades: The total number of losing trades generated by the strategy. Winning Trades: The total number of winning trades generated by the strategy. Total Trades: Total number of taken traders visible your charts. Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign. - Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month. - Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations. - OFF: Hides the performance table. Labels: - OFF: Hides labels in the performance table. - PnL: Shows the profit and loss of each trade individually, providing detailed insights into the performance of each trade. - Range: Shows the range length and Average Day Range (ADR), offering additional context about market conditions during each trade. Profit Color: - Allows users to set the color for representing profit in the performance table, helping to quickly distinguish profitable periods. Loss Color: - Allows users to set the color for representing loss in the performance table, helping to quickly identify loss-making periods. These customizable tables provide traders with flexible and detailed performance analysis, aiding in better strategy evaluation and optimization. ----- User-input styles and customizations: To facilitate studying historical data, all conditions and rules can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions. Please note that all background colors in the style are disabled by default to enhance visualization. ----- How to Use This Algobuilder to Create a Profitable Edge and System: Choose Your Strategy mode: - Decide whether you are creating an investing strategy or a trading strategy. Select a Market: - Choose a one-sided market such as stocks, indices, or cryptocurrencies. Historical Data: - Ensure the historical data covers at least 10 years of price action for robust backtesting. Timeframe Selection: - Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions on your profits. Set Commission and Slippage: - Properly set the commission and slippage in the strategy properties according to your broker or prop firm specifications. Parameter Optimization: - Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester. Trade Count: - Ensure the number of trades is 100 or more; the higher, the better for statistical significance. Positive Average Trade: - Make sure the average trade value is above zero. (An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.) Performance Metrics: - Look for a high profit factor, MAR (Mar Ratio), CAGR (Compound Annual Growth Rate), and net profit with minimum drawdown. Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance. Refinement and Optimization: - Try out different markets and timeframes. - Continue working on refining your edge using the available filters and components to further optimize your strategy. Automation: - Once you’re confident in your strategy, you can use the automation section to connect the algorithm to your broker or prop firm. - Trade a fully automated and backtested trading strategy, allowing for hands-free execution and management. ----- What makes this strategy original? 1. Incorporating direct integration of probabilities into the strategy. 2. Leveraging market sentiment to construct a profitable approach. 3. Utilizing built-in market structure-based trailing stop-loss mechanisms across various timeframes. 4. Offering both investing and trading strategies, facilitating optimization from different perspectives. 5. Automation for efficient execution. 6. Providing a summary table for instant access to key parameters of the strategy. ----- How to use automation? For Traders: 1. Ensure the strategy parameters are properly set based on your optimized parameters. 2. Enter your PineConnector License ID in the designated field. 3. Specify the desired risk level. 4. Provide the Metatrader symbol. 5. Check for chart updates to ensure the automation table appears on the top right corner, displaying your License ID, risk, and symbol. 6. Set up an alert with the strategy selected as Condition and the Message as {{strategy.order.alert_message}}. 7. Activate the Webhook URL in the Notifications section, setting it as the official PineConnector webhook address. 8. Double-check all settings on PineConnector to ensure the connection is successful. 9. Create the alert for entry/exit automation. For Investors: 1. Ensure the strategy parameters are properly set based on your optimized parameters. 2. Choose "Investing" in the user-input settings. 3. Create an alert with a specified name. 4. Customize the notifications tab to receive alerts via email. 5. Buying/selling alerts will be triggered instantly upon entry or exit order execution. ---- Strategy Properties This script backtest is done on 4H COINBASE:BTCUSD , using the following backtesting properties: Balance: $5000 Order Size: 10% of the equity Risk % per trade: 1% Commission: 0.04% (Default commission percentage according to TradingView competitions rules) Slippage: 75 ticks Pyramiding: 2 ----- Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited. By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.

Strategi Pine Script®

oleh Fractalyst

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E&M Strategy Box with Stock Screener ENGLISH “E&M Strategy Box” is an indicator created to combine different strategies. Different strategies are planned to be added in the future. General Features: First, the related strategy is selected from the "Strategy Type" tab. There are 2 different strategy choices. • Trend : For Most and OTT Indicator • MA : For Moving Average Indicator 1- Trend Strategy Options Within this section, there are 2 important indicators such as Most and OTT. And with the help of these indicators, buy-sell signals are formed. • Show Trend Signals : Show Trend and Support Line Signal? • Show Trend Crossing Signals : Show Buy/Sell Signal? 2- MA Strategy Options There are different moving averages in this section. And in line with cross of these moving averages, buy-sell signals are formed. - T3 - EMA - SMA - DEMA - TEMA - WMA - VWMA - SMMA - HMA - VMA - ZLEMA Many different moving environments will be added over time. • Show MA Signals : Show MA Signal? • Show MA Crossing Signals : Show Buy/Sell Signal? 3- Stock Screener Options One of the most important features of the indicator is that it scans among 40 symbols given the receive signal in line with the conditions mentioned above and lists the results. Stock screener is carried out over the relevant time period for the active symbol. Stock Screener On / Off : Enable the Stock Screener Feature Last Bar Back : How many bars back 4- Strategy Tester Options The activation of the strategy test feature in Tradingview and at the same time, by giving the standard deviation value during the buy-sell signals, false buy-sell signals are reduced in the horizontal market. With the activation of the test feature, some additional statistical information about performance is also provided. Enable Strategy Tester : Enable the Strategy Tester Feature Standard Deviation Period : Standard Deviation Period Standard Deviation Value : Standard Deviation Value 5- Backtest Input Options With the activation of the strategy test feature, it is the section in which time intervals the relevant back tests are entered. As the values change, the corresponding performance values also change dynamically. 6- Support & Resistance Options It is the section where the parameters are entered in order to show the support and resistance points in the related period while applying buy and sell strategies. Also, High-Low values are shown on the graph in this section. Pivot Length : Pivot Length Show Pivot Level : Show Pivot Level Show S / R Level : Show Support and Resistance Level 7- All Symbol Lists It is the section where the symbol information entered. If you have different strategies and you share them, related additions can be made as a strategy within the code. TÜRKÇE “E&M Strategy Box”, farklı stratejileri biraraya getirmek için oluşturulmuş bir indikatördür. İleriki zamanlarda farklı farklı stratejilerin eklenmesi düşünülmektedir. Genel Özellikler: İlk olarak “Strategy Type” sekmesinden ilgili stratejisi seçimi yapılır. 2 farklı stratejimi seçimi bulunmaktadır. • Trend : Most ve OTT indikatörleri için • MA : Hareketli ortalama indikatörleri için 1- Trend Strategy Options: Bu bölüm içerisinde Most ve OTT gibi 2 önemli indikatör bulunmaktadır. Ve bu indikatörler yardımıyla al-sat sinyalleri oluşmaktadır. • Show Trend Signals : Trend ve Destek sinyali görüntülensin mi? • Show Trend Crossing Signals : Al-Sat mesajı görüntülensin mi? 2- MA Strategy Options: Bu bölüm içerisinde birbirinden farklı hareketli ortalamalar bulunmaktadır. Ve bu hareketli ortalamaların kesişimleri doğrultusunda al-sat sinyalleri oluşmaktadır. Hareketli ortamalar: - T3 - EMA - SMA - DEMA - TEMA - WMA - VWMA - SMMA - HMA - VMA - ZLEMA Zaman içerisinde çok daha farklı hareketli ortamalar eklenecektir. • Show MA Signals : HO sinyalleri görüntülensin mi? • Show MA Crossing Signals : Al-Sat mesajı görüntülensin mi? 3- Stock Screener Options Indikatörün en önemli özelliklerinden biri de yukarıda belirtilen koşullar doğrultusunda al sinyali verilen 40 sembol arasından tarama yapması ve sonuçları listelemesidir. Hisse taraması aktif hisse için ilgili zaman periyodu üzerinden yapılmaktadır. Stock Screener On/Off : Hisse tarama özelliğinin aktive edilmesi Last Bar Back : Kaç bar öncesi 4- Strategy Tester Options Tradingview içerisinde yer alan strateji test özelliğinin aktive edilmesi ve aynı zamanda al-sat sinyalleri sırasında, standart sapma değeri verilerek, yatay piyasada yanlış al sat sinyallerinin azaltılması sağlanmıştır. Test özelliğinin aktive edilmesi ile birlikte performans ile ilgili bazı ek istatistiki bilgiler de sunulmaktadır. Enable Strategy Tester : Strateji test özelliğinin aktive edilmesi Standart Deviation Period : Standart Sapma Peryodu Standart Deviation Value : Standart Sapma Değeri 5- Backtest Input Options: Strateji test özelliğinin aktive edilmesi ile birlikte, hangi zaman aralıklarında ilgili geriye dönük testlerin girişlerinin yapıldığı bölümdür. Değerler değiştikçe, ilgili performans değerleri de dinamik olarak değişmektedir. 6- Support & Resistance Options Al ve sat stratejileri uygularken, ilgili peryotta destek ve direnç noktalarının da gösterimi için parametrelerin giriş yapıldığı bölümdür. Ayrıca bu bölüm içerisinde Yüksek Düşük (High-Low) değerleri de grafik üzerinde gösterilmektedir. Pivot Length : Pivot Uzunluğu Show Pivot Level : Pivot Seviyelerinin Gösterimi Show S/R Level : Destek ve Direnç Sevilerinin Gösterimi 7- All Symbol Lists Yukarıda belirtilen tarama koşullarının hangi hisseler üzerinden yapılmak istendiği ile ilgili hisse bilgilerinin giriş yapıldığı bölümdür. Farklı stratejileriniz varsa ve paylaşmanız durumunda kod içerisinde strateji olarak ilgili eklemeler yapılabilir.

Strategi Pine Script®

oleh RandEvolution

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Third eye • Strategy Third eye • Strategy – User Guide 1. Idea & Concept Third eye • Strategy combines three things into one system: Ichimoku Cloud – to define market regime and support/resistance. Moving Average (trend filter) – to trade only in the dominant direction. CCI (Commodity Channel Index) – to generate precise entry signals on momentum breakouts. The script is a strategy, not an indicator: it can backtest entries, exits, SL, TP and BreakEven logic automatically. 2. Indicators Used 2.1 Ichimoku Standard Ichimoku settings (by default 9/26/52/26) are used: Conversion Line (Tenkan-sen) Base Line (Kijun-sen) Leading Span A & B (Kumo Cloud) Lagging Span is calculated but hidden from the chart (for visual simplicity). From the cloud we derive: kumoTop – top of the cloud under current price. kumoBottom – bottom of the cloud under current price. Flags: is_above_kumo – price above the cloud. is_below_kumo – price below the cloud. is_in_kumo – price inside the cloud. These conditions are used as trend / regime filters and for stop-loss & trailing stops. 2.2 Moving Average You can optionally display and use a trend MA: Types: SMA, EMA, DEMA, WMA Length: configurable (default 200) Source: default close Filter idea: If MA Direction Filter is ON: When Close > MA → strategy allows only Long signals. When Close < MA → strategy allows only Short signals. The MA is plotted on the chart (if enabled). 2.3 CCI & Panel The CCI (Commodity Channel Index) is used for entry timing: CCI length and source are configurable (default length 20, source hlc3). Two thresholds: CCI Upper Threshold (Long) – default +100 CCI Lower Threshold (Short) – default –100 Signals: Long signal: CCI crosses up through the upper threshold cci_val < upper_threshold and cci_val > upper_threshold Short signal: CCI crosses down through the lower threshold cci_val > lower_threshold and cci_val < lower_threshold There is a panel (table) in the bottom-right corner: Shows current CCI value. Shows filter status as colored dots: Green = filter enabled and passed. Red = filter enabled and blocking trades. Gray = filter is disabled. Filters shown in the panel: Ichimoku Cloud filter (Long/Short) Ichimoku Lines filter (Conversion/Base vs Cloud) MA Direction filter 3. Filters & Trade Direction All filters can be turned ON/OFF independently. 3.1 Ichimoku Cloud Filter Purpose: trade only when price is clearly above or below the Kumo. Long Cloud Filter (Use Ichimoku Cloud Filter) – when enabled: Long trades only if close > cloud top. Short Cloud Filter – when enabled: Short trades only if close < cloud bottom. If the cloud filter is disabled, this condition is ignored. 3.2 Ichimoku Lines Above/Below Cloud Purpose: stronger trend confirmation: Ichimoku lines should also be on the “correct” side of the cloud. Long Lines Filter: Long allowed only if Conversion Line and Base Line are both above the cloud. Short Lines Filter: Short allowed only if both lines are below the cloud. If this filter is OFF, the conditions are not checked. 3.3 MA Direction Filter As described above: When ON: Close > MA → only Longs. Close < MA → only Shorts. 4. Anti-Re-Entry Logic (Cloud Touch Reset) The strategy uses internal flags to avoid continuous re-entries in the same direction without a reset. Two flags: allowLong allowShort After a Long entry, allowLong is set to false, allowShort to true. After a Short entry, allowShort is set to false, allowLong to true. Flags are reset when price touches the Kumo: If Low goes into the cloud → allowLong = true If High goes into the cloud → allowShort = true If Close is inside the cloud → both allowLong and allowShort are set to true There is a key option: Wait Position Close Before Flag Reset If ON: cloud touch will reset flags only when there is no open position. If OFF: flags can be reset even while a trade is open. This gives a kind of regime-based re-entry control: after a trend leg, you wait for a “cloud interaction” to allow new signals. 5. Risk Management All risk management is handled inside the strategy. 5.1 Position Sizing Order Size % of Equity – default 10% The strategy calculates: position_value = equity * (Order Size % / 100) position_qty = position_value / close So position size automatically adapts to your current equity. 5.2 Take Profit Modes You can choose one of two TP modes: Percent Fibonacci 5.2.1 Percent Mode Single Take Profit at X% from entry (default 2%). For Long: TP = entry_price * (1 + tp_pct / 100) For Short: TP = entry_price * (1 - tp_pct / 100) One strategy.exit per side is used: "Long TP/SL" and "Short TP/SL". 5.2.2 Fibonacci Mode (2 partial TPs) In this mode, TP levels are based on a virtual Fib-style extension between entry and stop-loss. Inputs: Fib TP1 Level (default 1.618) Fib TP2 Level (default 2.5) TP1 Share % (Fib) (default 50%) TP2 share is automatically 100% - TP1 share. Process for Long: Compute a reference Stop (see SL section below) → sl_for_fib. Compute distance: dist = entry_price - sl_for_fib. TP levels: TP1 = entry_price + dist * (Fib TP1 Level - 1) TP2 = entry_price + dist * (Fib TP2 Level - 1) For Short, the logic is mirrored. Two exits are used: TP1 – closes TP1 share % of position. TP2 – closes remaining TP2 share %. Same stop is used for both partial exits. 5.3 Stop-Loss Modes You can choose one of three Stop Loss modes: Stable – fixed % from entry. Ichimoku – fixed level derived from the Kumo. Ichimoku Trailing – dynamic SL following the cloud. 5.3.1 Stable SL For Long: SL = entry_price * (1 - Stable SL % / 100) For Short: SL = entry_price * (1 + Stable SL % / 100) Used both for Percent TP mode and as reference for Fib TP if Kumo is not available. 5.3.2 Ichimoku SL (fixed, non-trailing) At the time of a new trade: For Long: Base SL = cloud bottom minus small offset (%) For Short: Base SL = cloud top plus small offset (%) The offset is configurable: Ichimoku SL Offset %. Once computed, that SL level is fixed for this trade. 5.3.3 Ichimoku Trailing SL Similar to Ichimoku SL, but recomputed each bar: For Long: SL = cloud bottom – offset For Short: SL = cloud top + offset A red trailing SL line is drawn on the chart to visualize current stop level. This trailing SL is also used as reference for BreakEven and for Fib TP distance. 6. BreakEven Logic (with BE Lines) BreakEven is optional and supports two modes: Percent Fibonacci Inputs: Percent mode: BE Trigger % (from entry) – move SL to BE when price goes this % in profit. BE Offset % from entry – SL will be set to entry ± this offset. Fibonacci mode: BE Fib Level – Fib level at which BE will be activated (default 1.618, same style as TP). BE Offset % from entry – how far from entry to place BE stop. The logic: Before BE is triggered, SL follows its normal mode (Stable/Ichimoku/Ichimoku Trailing). When BE triggers: For Long: New SL = max(current SL, BE SL). For Short: New SL = min(current SL, BE SL). This means BE will never loosen the stop – only tighten it. When BE is activated, the strategy draws a violet horizontal line at the BreakEven level (once per trade). BE state is cleared when the position is closed or when a new position is opened. 7. Entry & Exit Logic (Summary) 7.1 Long Entry Conditions for a Long: CCI signal: CCI crosses up through the upper threshold. Ichimoku Cloud Filter (optional): If enabled → price must be above the Kumo. Ichimoku Lines Filter (optional): If enabled → Conversion Line and Base Line must be above the Kumo. MA Direction Filter (optional): If enabled → Close must be above the chosen MA. Anti-re-entry flag: allowLong must be true (cloud-based reset). Position check: Long entries are allowed when current position size ≤ 0 (so it can also reverse from short to long). If all these conditions are true, the strategy sends: strategy.entry("Long", strategy.long, qty = calculated_qty) After entry: allowLong = false allowShort = true 7.2 Short Entry Same structure, mirrored: CCI signal: CCI crosses down through the lower threshold. Cloud filter: price must be below cloud (if enabled). Lines filter: conversion & base must be below cloud (if enabled). MA filter: Close must be below MA (if enabled). allowShort must be true. Position check: position size ≥ 0 (allows reversal from long to short). Then: strategy.entry("Short", strategy.short, qty = calculated_qty) Flags update: allowShort = false allowLong = true 7.3 Exits While in a position: The strategy continuously recalculates SL (depending on chosen mode) and, in Percent mode, TP. In Fib mode, fixed TP levels are computed at entry. BreakEven may raise/tighten the SL if its conditions are met. Exits are executed via strategy.exit: Percent mode: one TP+SL exit per side. Fib mode: two partial exits (TP1 and TP2) sharing the same SL. At position open, the script also draws visual lines: White line — entry price. Green line(s) — TP level(s). Red line — SL (if not using Ichimoku Trailing; with trailing, the red line is updated dynamically). Maximum of 30 lines are kept to avoid clutter. 8. How to Use the Strategy Choose market & timeframe Works well on trending instruments. Try crypto, FX or indices on H1–H4, or intraday if you prefer more trades. Adjust Ichimoku settings Keep defaults (9/26/52/26) or adapt to your timeframe. Configure Moving Average Typical: EMA 200 as a trend filter. Turn MA Direction Filter ON if you want to trade only with the main trend. Set CCI thresholds Default ±100 is classic. Lower thresholds → more signals, higher noise. Higher thresholds → fewer but stronger signals. Enable/disable filters Turn on Ichimoku Cloud and Ichimoku Lines if you want only “clean” trend trades. Use Wait Position Close Before Flag Reset to control how often re-entries are allowed. Choose TP & SL mode Percent mode is simpler and easier to understand. Fibonacci mode is more advanced: it aligns TP levels with the distance to stop, giving asymmetric RR setups (two partial TPs). Choose Stable SL for fixed-risk trades, or Ichimoku / Ichimoku Trailing to tie stops to the cloud structure. Set BreakEven Enable BE if you want to lock in risk-free trades after a certain move. Percent mode is straightforward; Fib mode keeps BreakEven in harmony with your Fib TP setup. Run Backtest & Optimize Press “Add to chart” → go to Strategy Tester. Adjust parameters to your market and timeframe. Look at equity curve, PF, drawdown, average trade, etc. Live / Paper Trading After you’re satisfied with backtest results, use the strategy to generate signals. You can mirror entries/exits manually or connect them to alerts (if you build an alert-based execution layer).

Strategi Pine Script®

oleh RezzoRedPriest

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Multi Channel GRID & DCA LTF [trade_lexx]Multi Channel GRID & DCA LTF Usage Guide Part 1: The concept and general possibilities of the "Multi Channel GRID & DCA LTF" strategy Introduction Welcome to the guide to "Multi Channel GRID & DCA LTF", a powerful and versatile automated trading strategy for the TradingView platform. This tool was developed for traders who are looking for flexibility, control and a high degree of adaptability to various market conditions. The strategy is based on a hybrid approach that combines two popular and time-tested techniques.: 1. GRID (grid trading): The classic method of averaging a position is by placing a grid of limit orders. 2. DCA (Dollar Cost averaging): Smart position averaging based on signals from external indicators. However, "Multi Channel GRID & DCA LTF" goes far beyond the simple combination of these two techniques. The strategy includes a number of unique and innovative features, such as cascading MultiGRID grids for dealing with extreme volatility, Channel Mode range trading mode for profiting from sideways movement, and Low Time Frame analysis (LTF) to achieve surgical accuracy in backtesting. Deep customization options for risk management, capital, take profits, and stop losses allow you to configure a strategy for almost any trading style, asset, and timeframe. The basic idea: How does it work? Let's take a detailed look at each of the key concepts embedded in the logic of the strategy. 1. GRID — Automatic placement of buy and sell orders at certain price intervals. This is a fundamental mode of operation. Its main goal is to systematically improve the average entry price for a position if the market is going against you. * The principle of operation: After opening the base (first) order (`BO`), the strategy automatically places a series of pending limit orders (here they are called "safety orders" or "SO") at certain price intervals. For a long position, orders are placed below the entry price, and for a short position, orders are placed higher. * Target: When the price moves against an open position, it consistently hits and executes safety orders. Each such execution adds additional volume to the position at a more favorable price, thereby shifting the overall average entry price (`position_avg_price') closer to the current market price. This means that a much smaller corrective movement will be required to gain ground. * Flexibility: You have full control over the geometry of the grid: the number of safety orders, the percentage distance between them (`SO Step`), and you can even set a coefficient that will increase this step for each subsequent order (`SO Multiplier`), creating an expanding grid. 2. DCA (Signal Averaging) — Smart Averaging This mode adds an additional layer of analysis to the averaging process. Instead of just buying/selling at the set price levels, the strategy waits for a confirmation signal. * Working principle: You can connect any external indicator (for example, RSI, CCI, or even your own complex signal system) to the strategy, which outputs numerical values. As standard, 1 is used for a long signal, and -1 is used for a short signal. The strategy will place the next averaging order only at the moment when it receives the appropriate signal. * Goal: To average a position not just during a fall (or a rise for a short), but at the moments that your main trading system considers the most favorable for this. This allows you to avoid "catching falling knives" and enter only if there are good reasons. 3. Hybrid Mode (GRID+DCA) is the best of the previous two modes This mode is designed for maximum filtering and control. It requires two conditions to be fulfilled simultaneously. * Working principle: The safety order will be executed only if the price has reached the calculated grid level and a confirmation signal has been received from your external indicator. If a confirmation signal is received from an external indicator, the next calculated grid level activates the limit order. * Goal: To create the most reliable averaging system that protects against premature entries and requires double confirmation (both by price and indicator) before increasing the position size. 4. MultiGRID — Adaptation to extreme volatility This is one of the most powerful and unique features of a strategy designed to survive and make a profit in the face of strong, protracted trends or "black swans". * The problem it solves: The usual grid of orders has a limited depth. If the price goes beyond the last safety order, the strategy loses the opportunity to average and becomes vulnerable. * The principle of operation: The MultiGRID function allows you to create "cascades" — several grids following one another. When all the orders of the first grid are executed, the strategy does not stop. Instead, she can activate the second, third (and so on) a grid of orders. The new grid can be activated by one of two triggers: 1. Offset: The new grid is activated when the price passes another set percentage deviation from the last executed order. 2. Signal: The new grid is activated when a signal is received from an external indicator. * Goal: To significantly expand the working range of the strategy. This allows it to adapt to strong market movements that would "break" the usual grid, and continue to effectively average a position at a much greater depth of decline or growth. 5. Channel Mode — Trading in the range This feature turns a standard averaging strategy into a machine for "farming" profits within a price channel that is formed during a sideways market movement. * The problem it solves: In the standard grid strategy, after partially closing a take profit position, the volume of this part "leaves" the trade until the deal is fully closed. You are missing the opportunity to reuse this capital. * Operating principle: When Channel Mode is enabled, the following happens. Suppose the price went against you, executed several safety orders, and then turned around and reached one of the partial take profits. At this point, the strategy is: 1. Fixes the profit, as it should be. 2. Instantly places a new limit order to buy (or sell for a short) at exactly the same price level where the last triggered safety order was executed. The volume of this order is equal to the volume of the part that was just closed for take profit. 3. If the price goes down again and executes this "repeat" order, the strategy immediately sets a corresponding take profit for it at the level where the previous profit was taken. * Goal: To create a continuous buy-sell cycle within the local range (channel). The lower limit of the channel is the price of the last averaging, and the upper limit is the price of a partial take profit. This allows you to repeatedly profit from sideways price fluctuations, without waiting for the full closure of the main, large transaction. 6. LTF (Lower Timeframe Analysis) — Surgical precision of backtesting This feature is critically important for obtaining reliable results during historical testing (backtesting) of grid strategies. * The problem it solves: The standard testing mechanism in TradingView has a serious limitation. Working, for example, on a 4-hour chart, he sees only 4 candle points: Open, High, Low and Close. He does not know in what order the price moved within these 4 hours. He could have touched High first and then Low, or vice versa. For grid strategies, this is fatal — the engine can show that a take profit has been executed, although in reality the price first went down, collected the entire grid of orders and only then turned around. * How it works: When you turn on the LTF mode, the strategy for each candle on your main chart (for example, 4H) requests and analyzes all candles from the lower timeframe you specified (for example, 1-minute). Then it virtually trades the entire price path for these minute candles, executing orders, take profits and stop losses in the sequence in which they would occur in reality. It works in the single take profit mode of the Grid strategy. * Goal: To provide the most realistic and reliable backtest that reflects the real dynamics of the market. This allows you to avoid false expectations and accurately assess the potential performance of the strategy. // ------------------------ Part 2: Detailed description of the strategy settings This section is your main guide to all the switches and options available in the strategy. Understanding each setting is the key to unlocking the full potential of this powerful tool. 1. 🛡️ Risk Management 🛡️ This group contains fundamental parameters that determine the basic logic of risk management and the geometry of grid orders. * Strategy type: Determines the direction of transactions. * Long: The strategy will only open long positions (buy). * Short: The strategy will only open short positions (sell). * Both: The strategy will work both ways, opening long or short depending on the incoming signal. * SO Count: Sets the maximum number of Safety (averaging) Orders (SO) that the strategy will place within the same grid. If you have MultiGRID enabled, this number applies to each individual grid. * SO Step (%): This is the base percentage deviation from the entry price at which the first safety order will be placed. For example, at a value of 0.5, the first SO in a long trade will be placed 0.5% lower than the opening price of the base order. * SO Multiplier: A coefficient that exponentially increases the step for each subsequent safety order. This allows you to create an expanding grid where averaging orders are placed further and further apart, which is effective with strong and accelerating price movements. * *The step formula for the nth order*: Step(N) = (SO Step) * (SO Multiplier ^(N-1)). * If the value is 1, all steps will be the same. * With a value of 1.6, the step of the second SO will be 1.6 times larger than the first, the step of the third will be 1.6 times larger than the second, and so on. * 1️⃣ TP/SL: These are simplified settings for quick configuration. They allow you to turn on/off the main take profit and stop loss and set basic percentage values for them. More detailed settings for these parameters can be found in the relevant sections below. // ------------------------ 2. 💰 Money Management 💰 Everything related to position size, leverage, and capital is configured here. * Volume BO (Base Order): Determines the size of the trade's opening order. * Volume BO: A fixed amount in the quote currency (for example, in USDT). * USDT (check mark): Manages the information in the comments to the orders. If enabled, the volume of orders in USDT will be displayed in the comments. This is convenient for visual analysis and for sending the amount of USDT by the placeholder {{strategy.order.comment}} via webhooks when connecting the strategy to the exchange or trading terminals. * or % of deposit: The amount calculated as a percentage of the available capital of the strategy. The check mark to the right of this field enables this mode. Important: using a percentage activates the effect of compounding (compound interest), as the amount of each new transaction will be automatically recalculated based on the current capital (initial capital + profit/loss). If enabled, the percentage of orders will be displayed in the comments. This is convenient for visual analysis and for sending percentages on the placeholder {{strategy.order.comment}} via webhooks when connecting the strategy to the stock exchange, trading terminals, or creating Copy trading. * Martingale: The coefficient applied to the volume of orders. It increases the size of each subsequent insurance order compared to the base one. * Volume formula for the nth SO: Volume SO (N) = (Volume BO) * (Martingale^N). * With a value of 1.2, the volume of the first SO will be 1.2 times greater than the base, the second — 1.44 times (`1.2 * 1.2`) and so on. * Leverage: Specify the size of your leverage. This parameter is used exclusively for calculating and displaying the approximate liquidation price. It does not affect the size of positions, but it helps to visually assess the risks. * Liquidation: Enables or disables the calculation and display of the liquidation line on the chart. * Margin type: Allows you to select a method for calculating the liquidation price, simulating the logic of exchanges: * Isolated: The liquidation price is calculated based on the size and leverage of the current open position only. * Cross: The calculation simulates using the entire available balance to maintain a position. In the strategy, the liquidation price is calculated as the level at which the loss on the current transaction is equal to the current capital. * Commission (%): Specify the percentage of your exchange's commission per transaction. The correct value of this parameter is crucial for obtaining realistic backtest results. // ------------------------ 3. 🕸️ Grid Management 🕸️ This group is responsible for the logic of safety orders and advanced mechanics such as Channel Mode and MultiGRID. * SO Type: Defines the logic of placing averaging orders. * GRID: Classic grid. All safety orders are placed in advance as limit orders. * DCA: Signal averaging. The strategy is waiting for a signal from an external indicator to place a market averaging order. * GRID+DCA: Hybrid. The strategy waits for a signal, and if it arrives, places a limit order at the appropriate price level of the grid or executes a market order if the signal has arrived below the limit order level. * Signal for SO: A data source (indicator) that will be used for signals in DCA and GRID+DCA modes. * ↔️ Channel Mode: When this option is enabled, the strategy tries to trade in a sideways range. After partially closing a take profit position, it immediately places a limit order for re-entry at the price of the last triggered safety order. This creates a buy-sell cycle within the local channel. * Best Price Only: This filter adds an additional condition for averaging in DCA and MultiGRID modes (when it operates on a signal). The next averaging order or a new grid will be activated only if the current price is more favorable (lower for long, higher for short) than the price of the previous entry. * 🧩 MultiGRID ⮕ Enables cascading grid mode. * Grid Count: The total number of grids that can be activated sequentially. * Offset: Percentage deviation from the price of the last order of the previous grid. When this margin is reached, the following grid of orders is activated (this mode does not require a signal). * Or signal: Allows you to use the signal from an external indicator as a trigger to activate the next grid. The checkmark on the right turns on this mode. // ------------------------ 4. 🎯 Entry and Stop 🎯 This group of settings allows you to fine-tune the conditions for starting a new trade and all aspects related to protective stop orders, including the complex mechanics of trailing and managing SL after partial take profits. * 🎯 Signal: A data source (indicator) that will be used to determine when to enter a trade. The strategy expects a value of 1 for the start of a long trade and -1 for a short trade. * Min Bars: Sets the minimum number of candles that must pass from the moment of opening the previous trade to the moment of opening the next one. A value of 0 disables this filter. This is a useful tool to prevent overly frequent entries in a "noisy" market. * Non-stop: If this option is enabled, the strategy ignores the Entry Signal and opens a new trade immediately after closing the previous one (taking into account the Min Bars filter, if it is set). This turns the strategy into a constantly working mechanism that is always on the market. * 🛑 SL Type: Defines the base price from which the stop loss percentage will be calculated. The stop loss in the first section must be enabled for this block of settings to work. * From the entry point: SL is always calculated from the opening price of the very first base order. It remains static throughout the entire transaction unless it is moved by other functions. * From breakeven line: SL is dynamically recalculated and shifted each time a safety order is executed. It always follows the average price of the position, being at a given percentage distance from it. * From last executed SO: SL is recalculated from the price of the last executed order, whether it is a base or a safety order. * From last SO: SL is calculated from the price of the most recent possible safety order in the grid. This is usually the most remote and conservative type of SL. * Trailing SL Type: Defines the algorithm by which the stop loss will move after its activation. * Standard: Classic trailing. After activation, SL will follow the price at a fixed distance. * ATR: SL will follow the price at a distance equal to the value of the ATR indicator multiplied by the specified multiplier. * External Source: SL will follow any selected line of the third-party indicator. * Period and Multiplier: Common parameters for all types of trailing. * Source: The source of the line for the trailing SL of the third-party indicator. * Trailing SL after entry: The mode of activation of the trailing SL after entering the transaction * SL management after TP (sections 1️⃣, 2️⃣, 3️⃣): These three blocks allow you to create a complex stop loss management logic as profits are recorded. For each take profit level (TP1, TP2, TP3), you can configure: * SL BE / SL TP1 / SL TP2: When the corresponding TP is reached, the stop loss will be moved to the breakeven point (for TP1), to the TP1 price level (for TP2) or to the TP2 price level (for TP3). * Trailing SL: When the corresponding TP is reached, the trailing stop loss is activated according to the settings above. * By ↔️ Signal: A very powerful option. If it is enabled, the above action (SL transfer or trailing activation) will occur when the opposite trading signal is received from an external indicator. This allows you to protect profits or reduce losses if the market turns sharply, even before reaching the target. * SL Delay ⮕ Allows you to delay the activation of the stop loss. * Number of Bars: The Stop loss will be physically placed on the market only after the specified number of candles has passed since entering the trade. This can help to avoid "taking out" the stop with a random short movement (squiz) immediately after opening a position. * SL Block: Unique defensive mechanics for trading both ways (`Strategy Type: Both`). * Number of SL: If the strategy receives the specified number of stop losses in a row in one direction (for example, 2 stops long), it temporarily blocks the opportunity to open new trades in that direction. * Lock Reset mode: * By direction: The lock is lifted if a profitable trade is closed in the allowed direction or if a stop loss is triggered in the opposite direction. * First profit: The lock is lifted after closing any profitable transaction, regardless of its direction. // ------------------------ 5. ✅ Take Profit ✅ This group of settings provides comprehensive control over profit taking, from a simple take profit to a complex system of partial closures and trailing. * ✅ TP Type: Defines the base price for calculating the percentage deviation of the take profit. * From entry point: TP is calculated from the base order price. * From breakeven line: TP dynamically follows the average position price. * From last executed SO: TP is calculated from the price of the last executed order. * Filters for closing on signal * Only ➕: If TP is triggered by a signal, the deal will be closed only if it is in the black relative to the average price. * Or >TP: If TP is triggered by a signal, the trade will be closed only if the closing price is better than (or equal to) the estimated price of this TP. * TP type of trailing: Yes, take profit has a trailing too! It works differently than the SL trailing. * Standard / ATR: After the price touches the "virtual" TP level, the trailing is activated. He does not place a stop order, but begins to move away from the price, dynamically moving the limit order to close further and further in the profitable direction, allowing him to collect the maximum from the impulse movement. * External Source: TP will follow any selected line of the third-party indicator. * Period and Multiplier: Parameters for calculating the trailing margin TP. * Source: The source of the line for the trailing TP of the third-party indicator. * TP level settings (sections 1️⃣, 2️⃣, 3️⃣, 4️⃣): The strategy supports up to four independent take profit levels, which allows for a flexible system of partial commits. For each level, you can set: * TP: Enable the level and set its percentage deviation from the base price. * Size: What percentage of the current position will be closed when this level is reached. For the last active TP, this parameter is ignored, and 100% of the remaining position is closed. * Trailing TP: Enable the above-described trailing mechanism for this particular level. * Signal: Enable closing based on the signal from the external indicator for this level. * Or take: If both the closing on the signal and the limit order are enabled, then whatever comes first will work. * After SO: Activate this TP level only after the specified number of safety orders has been executed. This allows you to set closer targets for riskier (deeply averaged) positions. // ------------------------ 6. 🔬 GRID and MultiGrid Analysis on Lower TFs (LTF) 🔬 This group activates one of the most important functions for accurate testing of grid strategies. * Enable LTF Calculation ⮕ The main switch of the analysis mode on the lower timeframes. * Timeframe selection: A drop-down list where you can select a timeframe for detailed analysis. For example, if your main schedule is 1 hour, you can select 1 minute here. The strategy will emulate the trading of minute candles within each hour candle. ❗️Important: As mentioned in the first part, the use of this mode is critically necessary to obtain realistic backtest results, especially for strategies with a dense grid of orders. Without it, the results may be overly optimistic and not reflect the real dynamics of the market. It should be remembered that TradingView imposes a limit on the number of intra-bars (minor TF bars) that can be requested. This is usually about 100,000 bars. // ------------------------ 7. 🕘 Backtest Date Range 🕘 This group allows you to focus testing on a specific historical period. * Limit Date Range: Enables date filtering. * Start time: The date and time when the strategy will start analyzing and opening deals. * End time: The date and time after which the strategy will stop opening new deals and complete testing. // ------------------------ 8. 🎨 Visualization 🎨 All the options responsible for the appearance and information content of the chart are collected here. * Show PnL labels: Enables/disables the display of text labels with the result (profit/loss) after closing each trade. * Statistics Table: Enables/disables the main dashboard with detailed statistics on the results of the backtest. * Strategy Settings Table: Enables/disables an additional panel that summarizes all the key parameters of the current configuration. * Monthly Profit Table: Enables/disables a table with a breakdown of percentage returns by month and year. * Table settings: For each of the three tables, you can individually adjust the Text size and Table Position on the screen to position them as conveniently as possible. * Decimal places: Defines how many decimal places will be displayed in numeric values in tables and on labels. // ------------------------ 9. ✉️ Webhook Settings ✉️ This group is intended for traders who want to automate trading on strategy signals using third-party services and exchanges (for example, 3Commas, WunderTrading, Cryptorobotics, Cryptohopper, Bitsgap, Binance, ByBit, OKX, Pionex, Bitget or proprietary solutions). For each key event in the strategy, there is a separate switch and a text field: * Webhook for Open: Enable and set a message for the webhook that will be sent when the base order is opened. * Webhook for Averaging: A message sent when executing any insurance order. * Webhook for Take Profit: A message sent when closing on take profit (including partial ones). * Webhook for Stop-Loss: A message sent when a stop loss is closed. You can insert a JSON code or any other message format that your service requires for automation into the text fields. The strategy supports special placeholders (for example, `{{strategy.order.alert_message}}`), which allow you to dynamically insert the necessary data into the message, such as the amount of USDT or the percentage of the deposit for entry, averaging and take profit orders.

Strategi Pine Script®

oleh trade_lexx

Telah dikemas kini

Prop Firm Business Simulator The prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms. Now what is a modern day CFD Prop Firm? These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out. I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change. Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations. Now why is this tool helpful? Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal. While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in. I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using. How to use this tool It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that. //--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$ //--$$$$$--Strategy-- --$$$$$$--// ****************************************************************************************************************************** //--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$ length = input.int(20, minval=1, group="Keltner Channel Breakout") mult = input(2.0, "Multiplier", group="Keltner Channel Breakout") src = input(close, title="Source", group="Keltner Channel Breakout") exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout") BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout") atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout") esma(source, length)=> s = ta.sma(source, length) e = ta.ema(source, length) exp ? e : s ma = esma(src, length) rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length) upper = ma + rangema * mult lower = ma - rangema * mult //--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$ u = plot(upper, color=#2962FF, title="Upper", force_overlay=true) plot(ma, color=#2962FF, title="Basis", force_overlay=true) l = plot(lower, color=#2962FF, title="Lower", force_overlay=true) fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background") //--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$ riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout") le = high>upper ? false : true se = lowlower strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots) if se and upper>lower strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots) The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge. If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains. If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains. These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income. The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate. The daily drawdown limit get's reset every time there is a new dayofweek on chart. If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K. The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade. Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication: That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.

Strategi Pine Script®

oleh Honestcowboy

HilalimSB Strategy HilalimSB A Wedding Gift 🌙 What is HilalimSB🌙? First of all, as mentioned in the title, HilalimSB is a wedding gift. HilalimSB - Revealing the Secrets of the Trend HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm. Hilalim Algorithm and Fixed ATR Value: HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably. ATR Calculation Steps 1.True Range Calculation: + The True Range (TR) is the greatest of the following three values: 1. Current high minus current low 2. Current high minus previous close (absolute value) 3. Current low minus previous close (absolute value) 2.Average True Range (ATR) Calculation: -The initial ATR value is calculated as the average of the TR values over a specified period (typically 14 periods). -For subsequent periods, the ATR is calculated using the following formula: ATRt=(ATRt−1×(n−1)+TRt)/n Where: + ATRt is the ATR for the current period, + ATRt−1 is the ATR for the previous period, + TRt is the True Range for the current period, + n is the number of periods. Pine Script to Calculate ATR with User-Defined Length and Multiplier Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier: //@version=5 indicator("Custom ATR", overlay=false) // User-defined inputs X = input.int(14, minval=1, title="ATR Period (X)") Y = input.float(1.0, title="ATR Multiplier (Y)") // True Range calculation TR1 = high - low TR2 = math.abs(high - close ) TR3 = math.abs(low - close ) TR = math.max(TR1, math.max(TR2, TR3)) // ATR calculation ATR = ta.rma(TR, X) // Apply multiplier customATR = ATR * Y // Plot the ATR value plot(customATR, title="Custom ATR", color=color.blue, linewidth=2) This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters. HilalimSB's Distinction from Other ATR Indicators HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use. ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification. The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions. Visual Aesthetics and Clear Charts: HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience. Strong Signals and Buy/Sell Indicators: After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals. For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline. Technology and Innovation: HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience. Social Order and Intrinsic Motivation: Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely. What is HilalimSB Strategy🌙? HilalimSB Strategy is a strategy that is supported by the HilalimSB algorithm created by the creator of HilalimSB and continues transactions with take profit and stop loss levels determined by users who strategically and automatically open transactions as a result of the data it receives and automatically closes transactions under necessary conditions. It is a first in the tradingview world with its unique take profit and stop loss markings. HilalimSB Strategy is open to users' initiatives and is a trading strategy developed on BTC. What does the HilalimSB Strategy target? The main purpose of HilalimSB Strategy is to reduce the transaction load of traders and to be integrated into various brokerage firms and operated by automatic trading bots, and it is aimed to serve this purpose. In addition to the strategies currently available in the markets, HilalimSB Strategy offers a useful infrastructure to traders with its useful interface. HilalimSB Strategy, which was decided to be published as a result of various calculations, was offered to the users with its unique visual effects after the completion of the testing procedures under market conditions. HilalimSB Strategy and Heikin Ashi HilalimSB Strategy produces data in Heikin Ashi chart types, but since Heikin Ashi chart types have their own calculation method, HilalimSB Strategy has been published in a way that cannot produce data in this chart type due to HilalimSB Strategy's ideology of appealing to all types of users, and any confusion that may arise is prevented in this way. After the necessary conditions determined by the creator of HilalimSB are met, HilalimSB Heikin Ashi will be shared exclusively with invited users only, upon request, to users who request an invitation. Differences between HilalimSB Strategy and HilalimSB HilalimSB Strategy has been shared as a strategy and its features have been explained above. HilalimSB is a trading indicator and this is the main difference between them.We can explain it briefly this way. Here are the differences between indicators and strategies: 1.Purpose and Use: Indicators: Analyze market data to provide information about price movements and trends. They typically generate buy and sell signals and give traders clues about when to make trades in the market. Strategies: These are plans for trading based on specific rules. They use signals from indicators and other market data to execute buy and sell transactions. 2.Features: Indicators: Operate independently and are based on specific mathematical formulas. Examples include moving averages, RSI, and MACD. Strategies: Combine one or more indicators and other market analysis tools to create a comprehensive trading plan. This plan determines entry and exit points, risk management, and trade size. 3.Scope: Indicators: Are single analysis tools focusing on specific time frames or price movements. Strategies: Are comprehensive trading plans that typically involve multiple trades over a certain period. 4.Decision Making: Indicators: Provide information to traders and help in the decision-making process. Strategies: Are direct decision-making mechanisms that execute trades automatically according to predetermined rules. 5.Automation: Indicators: Are mostly interpreted manually and used based on the trader’s discretion. Strategies: Can be used in automated trading systems and execute trades automatically according to the set rules. The shared image is a 1-hour chart of BTCUSDC.P determined by the user as 1 percent take profit and 1 percent stop loss. And transactions were opened on Binance with the commission rate determined as 0.017 for the USDC trading pair. HilalimSB Strategy, which presents users with completely concrete data, has proven itself in testing processes and is a project of SB that aims to reach all user profiles.🌙

Strategi Pine Script®

oleh SuleymanB_

Telah dikemas kini

Ruckard TradingLatino This strategy tries to mimic TradingLatino strategy. The current implementation is beta. Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo. It's aimed at BTCUSDT pair and 4h timeframe. STRATEGY DEFAULT SETTINGS EXPLANATION max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false. calc_on_every_tick=false pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error. initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital. slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick) commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %. BACKGROUND Jaime Merino is a well known Youtuber focused on crypto trading His channel TradingLatino features monday to friday videos where he explains his strategy. JAIME MERINO STANCE ON BOTS Jaime Merino stance on bots (taken from memory out of a 2020 June video from him): '~ You know. They can program you a bot and it might work. But, there are some special situations that the bot would not be able to handle. And, I, as a human, I would handle it. And the bot wouldn't do it. ~' My long term target with this strategy script is add as many special situations as I can to the script so that it can match Jaime Merino behaviour even in non normal circumstances. My alternate target is learn Pine script and enjoy programming with it. WARNING This script might be bigger than other TradingView scripts. However, please, do not be confused because the current status is beta. This script has not been tested with real money. This is NOT an official strategy from Jaime Merino. This is NOT an official strategy from TradingLatino . net . HOW IT WORKS It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator to make its buy and sell decisions. Fast paced EMA being bigger than slow paced EMA (on higher timeframe) advices going long. Fast paced EMA being smaller than slow paced EMA (on higher timeframe) advices going short. It finally add many substrats that TradingLatino uses. SETTINGS __ SETTINGS - Basics ____ SETTINGS - Basics - ADX (ADX) Smoothing {14} (ADX) DI Length {14} (ADX) key level {23} ____ SETTINGS - Basics - LazyBear Squeeze Momentum (SQZMOM) BB Length {20} (SQZMOM) BB MultFactor {2.0} (SQZMOM) KC Length {20} (SQZMOM) KC MultFactor {1.5} (SQZMOM) Use TrueRange (KC) {True} ____ SETTINGS - Basics - EMAs (EMAS) EMA10 - Length {10} (EMAS) EMA10 - Source {close} (EMAS) EMA55 - Length {55} (EMAS) EMA55 - Source {close} ____ SETTINGS - Volume Profile Lowest and highest VPoC from last three days is used to know if an entry has a support VPVR of last 100 4h bars is also taken into account (VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC (VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day. (VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC. (VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC. (VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart. (VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals. (VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells. (VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it. (VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm). ____ SETTINGS - ADX Slope ADX Slope help us to understand if ADX has a positive slope, negative slope or it is rather still. (ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength (ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one. (ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one. (ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods. ____ SETTINGS - Next to EMA55 (NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55 (NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again. ____ SETTINGS - Stop Loss and Take Profit You can set a default stop loss or a default take profit. (STOPTAKE) Stop Loss % {7.0} (STOPTAKE) Take Profit % {2.0} ____ SETTINGS - Trailing Take Profit You can customize the default trailing take profit values (TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage (TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit. ____ SETTINGS - MAIN TURN ON/OFF OPTIONS (EMAS) Ignore advice based on emas {false}. (EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry. (SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator. (ADXSLOPE) Ignore advice based on ADX positive slope {false} (ADXSLOPE) Ignore advice based on ADX cut (23) {true} (STOPTAKE) Take Profit? {false}: Enables simple Take Profit. (STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss. (TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit. ____ SETTINGS - Strategy mode (STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'. ____ SETTINGS - Risk Management (RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'. (RISKM) Maximum loss per trade % {1.0}. (RISKM) Maximum loss per day % {6.0}. (RISKM) Maximum loss per week % {8.0}. (RISKM) Maximum loss per month % {10.0}. ____ SETTINGS - Decimals (DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange. EXTRA 1 - PRICE IS IN RANGE indicator (PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not. (PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians (PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection (PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator (SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis. (SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences. (SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences. EXTRA 3 - VOLUME PROFILE indicator WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart. (VP) Print recent profile {False}: Show Volume Profile indicator (VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart. EXTRA 4 - ZIGNALY SUPPORT (ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format. EXTRA 5 - DEBUG (DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered. HOW TO USE THIS STRATEGY BOT MODE: This is the default setting. PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off. NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator. ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy. ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy. ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it. JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement. EXTRA ADVICE It's advised that you use this strategy in addition to these two other indicators: * Squeeze Momentum Indicator * ADX so that your chart matches as close as possible to TradingLatino chart. ZIGNALY INTEGRATION This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration. ZIGNALY INTEGRATION - Email integration example What you would write in your alert message: ||{{strategy.order.alert_message}}||key=MYSECRETKEY|| ZIGNALY INTEGRATION - Webhook integration example What you would write in your alert message: { {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" } CREDITS I have reused and adapted some code from 'Directional Movement Index + ADX & Keylevel Support' study which it's from TradingView console user. I have reused and adapted some code from '3ema' study which it's from TradingView hunganhnguyen1193 user. I have reused and adapted some code from 'Squeeze Momentum Indicator ' study which it's from TradingView LazyBear user. I have reused and adapted some code from 'Strategy Tester EMA-SMA-RSI-MACD' study which it's from TradingView fikira user. I have reused and adapted some code from 'Support Resistance MTF' study which it's from TradingView LonesomeTheBlue user. I have reused and adapted some code from 'TF Segmented Linear Regression' study which it's from TradingView alexgrover user. I have reused and adapted some code from "Poor man's volume profile" study which it's from TradingView IldarAkhmetgaleev user. FEEDBACK Please check the strategy source code for more detailed information where, among others, I explain all of the substrats and if they are implemented or not. Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)? Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe. Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)? Any idea if you need to do something else rather than just reverse what Jaime does when longing? FREQUENTLY ASKED QUESTIONS FAQ1. Why are you giving this strategy for free? TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them. FAQ2. Seriously! Why are you giving this strategy for free? I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it. Now that everyone can contribute this is a win-win. FAQ3. How can I connect this strategy to my Exchange account? It seems that you can attach alerts to strategies. You might want to combine it with a paying account which enable Webhook URLs to work. I don't know how all of this works right now so I cannot give you advice on it. You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly, might end on you automating losses. FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy. You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'. FAQ5. Where can I learn more about your work on this strategy? Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet. FAQ6. How much leverage is applied in this strategy? No leverage. FAQ7. Any difference with original Jaime Merino strategy? Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing. FAQ8. Why this strategy return is so small? The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it. MENSAJE EN CASTELLANO En primer lugar se agradece feedback para mejorar la estrategia. Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo. Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés. CHISTE - CASTELLANO ¡Pero Jaime! ¡400.000! ¡Tu da mun!

Strategi Pine Script®

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The Best Strategy Template[LuciTech]Hello Traders, This is a powerful and flexible strategy template designed to help you create, backtest, and deploy your own custom trading strategies. This template is not a ready-to-use strategy but a framework that simplifies the development process by providing a wide range of pre-built features and functionalities. What It Does The LuciTech Strategy Template provides a robust foundation for building your own automated trading strategies. It includes a comprehensive set of features that are essential for any serious trading strategy, allowing you to focus on your unique trading logic without having to code everything from scratch. Key Features The LuciTech Strategy Template integrates several powerful features to enhance your strategy development: • Advanced Risk Management: This includes robust controls for defining your Risk Percentage per Trade, setting a precise Risk-to-Reward Ratio, and implementing an intelligent Breakeven Stop-Loss mechanism that automatically adjusts your stop to the entry price once a specified profit threshold is reached. These elements are crucial for capital preservation and consistent profitability. • Flexible Stop-Loss Options: The template offers adaptable stop-loss calculation methods, allowing you to choose between ATR-Based Stop-Loss, which dynamically adjusts to market volatility, and Candle-Based Stop-Loss, which uses structural price points from previous candles. This flexibility ensures the stop-loss strategy aligns with diverse trading styles. • Time-Based Filtering: Optimize your strategy's performance by restricting trading activity to specific hours of the day. This feature allows you to avoid unfavorable market conditions or focus on periods of higher liquidity and volatility relevant to your strategy. • Customizable Webhook Alerts: Stay informed with advanced notification capabilities. The template supports sending detailed webhook alerts in various JSON formats (Standard, Telegram, Concise Telegram) to external platforms, facilitating real-time monitoring and potential integration with automated trading systems. • Comprehensive Visual Customization: Enhance your analytical clarity with extensive visual options. You can customize the colors of entry, stop-loss, and take-profit lines, and effectively visualize market inefficiencies by displaying and customizing Fair Value Gap (FVG) boxes directly on your chart. How It Does It The LuciTech Strategy Template is meticulously crafted using Pine Script, TradingView's powerful and expressive programming language. The underlying architecture is designed for clarity and modularity, allowing for straightforward integration of your unique trading signals. At its core, the template operates by taking user-defined entry and exit conditions and then applying a sophisticated layer of risk management, position sizing, and trade execution logic. For instance, when a longCondition or shortCondition is met, the template dynamically calculates the appropriate position size. This calculation is based on your specified risk_percent of equity and the stop_distance (the distance between your entry price and the calculated stop-loss level). This ensures that each trade adheres to your predefined risk parameters, a critical component of disciplined trading. The flexibility in stop-loss calculation is achieved through a switch statement that evaluates the sl_type input. Whether you choose an ATR-based stop, which adapts to market volatility, or a candle-based stop, which uses structural price points, the template seamlessly integrates these methods. The ATR calculation itself is further refined by allowing various smoothing methods (RMA, SMA, EMA, WMA), providing granular control over how volatility is measured. Time-based filtering is implemented by comparing the current bar's time with user-defined start_hour, start_minute, end_hour, and end_minute inputs. This allows the strategy to activate or deactivate trading during specific market sessions or periods of the day, a valuable tool for optimizing performance and avoiding unfavorable conditions. Furthermore, the template incorporates advanced webhook alert functionality. When a trade is executed, a customizable JSON message is formatted based on your webhook_format selection (Standard, Telegram, or Concise Telegram) and sent via alert function. This enables seamless integration with external services for real-time notifications or even automated trade execution through third-party platforms. Visual feedback is paramount for understanding strategy behavior. The template utilizes plot and fill functions to clearly display entry prices, stop-loss levels, and take-profit targets directly on the chart. Customizable colors for these elements, along with dedicated options for Fair Value Gap (FVG) boxes, enhance the visual analysis during backtesting and live trading, making it easier to interpret the strategy's actions. How It's Original The LuciTech Strategy Template distinguishes itself in the crowded landscape of TradingView scripts through its unique combination of integrated, advanced risk management features, highly flexible stop-loss methodologies, and sophisticated alerting capabilities, all within a user-friendly and modular framework. While many templates offer basic entry/exit signal integration, LuciTech goes several steps further by providing a robust, ready-to-use infrastructure for managing the entire trade lifecycle once a signal is generated. Unlike templates that might require users to piece together various risk management components or code complex stop-loss logic from scratch, LuciTech offers these critical functionalities out-of-the-box. The inclusion of dynamic position sizing based on a user-defined risk percentage, a configurable risk-to-reward ratio, and an intelligent breakeven mechanism significantly elevates its utility. This comprehensive approach to capital preservation and profit targeting is a cornerstone of professional trading and is often overlooked or simplified in generic templates. Furthermore, the template's provision for multiple stop-loss calculation types—ATR-based for volatility adaptation, and candle-based for structural support/resistance—demonstrates a deep understanding of diverse trading strategies. The underlying code for these calculations is already implemented, saving developers considerable time and effort. The subtle yet powerful inclusion of FVG (Fair Value Gap) related inputs also hints at advanced price action concepts, offering a sophisticated layer of analysis and execution that is not commonly found in general-purpose templates. The advanced webhook alerting system, with its support for various JSON formats tailored for platforms like Telegram, showcases an originality in catering to the needs of modern, automated trading setups. This moves beyond simple TradingView pop-up alerts, enabling seamless integration with external systems for real-time trade monitoring and execution. This level of external connectivity and customizable data output is a significant differentiator. In essence, the LuciTech Strategy Template is original not just in its individual features, but in how these features are cohesively integrated to form a powerful, opinionated, yet highly adaptable system. It empowers traders to focus their creative energy on developing their core entry/exit signals, confident that the underlying framework will handle the complexities of risk management, trade execution, and external communication with precision and flexibility. It's a comprehensive solution designed to accelerate the development of robust and professional trading strategies. How to Modify the Logic to Apply Your Strategy The LuciTech Strategy Template is designed with modularity in mind, making it exceptionally straightforward to integrate your unique trading strategy logic. The template provides a clear separation between the core strategy management (risk, position sizing, exits) and the entry signal generation. This allows you to easily plug in your own buy and sell conditions without altering the robust underlying framework. Here’s a step-by-step guide on how to adapt the template to your specific trading strategy: 1. Locate the Strategy Logic Section: Open the Pine Script editor in TradingView and navigate to the section clearly marked with the comment //Strategy Logic Example:. This is where the template’s placeholder entry conditions (a simple moving average crossover) are defined. 2. Define Your Custom Entry Conditions: Within this section, you will find variables such as longCondition and shortCondition. These are boolean variables that determine when a long or short trade should be initiated. Replace the existing example logic with your own custom buy and sell conditions. Your conditions can be based on any combination of indicators, price action patterns, candlestick formations, or other market analysis techniques. For example, if your strategy involves a combination of RSI and MACD, you would define longCondition as (rsi > 50 and macd_line > signal_line) and shortCondition as (rsi < 50 and macd_line < signal_line). 3. Leverage the Template’s Built-in Features: Once your longCondition and shortCondition are defined, the rest of the template automatically takes over. The integrated risk management module will calculate the appropriate position size based on your Risk % input and the chosen Stop Loss Type. The Risk:Reward ratio will determine your take-profit levels, and the Breakeven at R feature will manage your stop-loss dynamically. The time filter (Use Time Filter) will ensure your trades only occur within your specified hours, and the webhook alerts will notify you of trade executions.

Strategi Pine Script®

oleh TradesLuci

Trendline Breaks with Multi Fibonacci Supertrend Strategy TMFS Strategy: Advanced Trendline Breakouts with Multi-Fibonacci Supertrend Elevate your algorithmic trading with institutional-grade signal confluence Strategy Genesis & Evolution This advanced trading system represents the culmination of a personal research journey, evolving from my custom " Multi Fibonacci Supertrend with Signals " indicator into a comprehensive trading strategy. Built upon the exceptional trendline detection methodology pioneered by LuxAlgo in their " Trendlines with Breaks " indicator, I've engineered a systematic framework that integrates multiple technical factors into a cohesive trading system. Core Fibonacci Principles At the heart of this strategy lies the Fibonacci sequence application to volatility measurement: // Fibonacci-based factors for multiple Supertrend calculations factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval = 0.01, step = 0.01) factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval = 0.01, step = 0.01) factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval = 0.01, step = 0.01) These precise Fibonacci ratios create a dynamic volatility envelope that adapts to changing market conditions while maintaining mathematical harmony with natural price movements. Dynamic Trendline Detection The strategy incorporates LuxAlgo's pioneering approach to trendline detection: // Pivotal swing detection (inspired by LuxAlgo) pivot_high = ta.pivothigh(swing_length, swing_length) pivot_low = ta.pivotlow(swing_length, swing_length) // Dynamic slope calculation using ATR slope = atr_value / swing_length * atr_multiplier // Update trendlines based on pivot detection if bool(pivot_high) upper_slope := slope upper_trendline := pivot_high else upper_trendline := nz(upper_trendline) - nz(upper_slope) This adaptive trendline approach automatically identifies key structural market boundaries, adjusting in real-time to evolving chart patterns. Breakout State Management The strategy implements sophisticated state tracking for breakout detection: // Track breakouts with state variables var int upper_breakout_state = 0 var int lower_breakout_state = 0 // Update breakout state when price crosses trendlines upper_breakout_state := bool(pivot_high) ? 0 : close > upper_trendline ? 1 : upper_breakout_state lower_breakout_state := bool(pivot_low) ? 0 : close < lower_trendline ? 1 : lower_breakout_state // Detect new breakouts (state transitions) bool new_upper_breakout = upper_breakout_state > upper_breakout_state bool new_lower_breakout = lower_breakout_state > lower_breakout_state This state-based approach enables precise identification of the exact moment when price breaks through a significant trendline. Multi-Factor Signal Confluence Entry signals require confirmation from multiple technical factors: // Define entry conditions with multi-factor confluence long_entry_condition = enable_long_positions and upper_breakout_state > upper_breakout_state and // New trendline breakout di_plus > di_minus and // Bullish DMI confirmation close > smoothed_trend // Price above Supertrend envelope // Execute trades only with full confirmation if long_entry_condition strategy.entry('L', strategy.long, comment = "LONG") This strict requirement for confluence significantly reduces false signals and improves the quality of trade entries. Advanced Risk Management The strategy includes sophisticated risk controls with multiple methodologies: // Calculate stop loss based on selected method get_long_stop_loss_price(base_price) => switch stop_loss_method 'PERC' => base_price * (1 - long_stop_loss_percent) 'ATR' => base_price - long_stop_loss_atr_multiplier * entry_atr 'RR' => base_price - (get_long_take_profit_price() - base_price) / long_risk_reward_ratio => na // Implement trailing functionality strategy.exit( id = 'Long Take Profit / Stop Loss', from_entry = 'L', qty_percent = take_profit_quantity_percent, limit = trailing_take_profit_enabled ? na : long_take_profit_price, stop = long_stop_loss_price, trail_price = trailing_take_profit_enabled ? long_take_profit_price : na, trail_offset = trailing_take_profit_enabled ? long_trailing_tp_step_ticks : na, comment = "TP/SL Triggered" ) This flexible approach adapts to varying market conditions while providing comprehensive downside protection. Performance Characteristics Rigorous backtesting demonstrates exceptional capital appreciation potential with impressive risk-adjusted metrics: Remarkable total return profile (1,517%+) Strong Sortino ratio (3.691) indicating superior downside risk control Profit factor of 1.924 across all trades (2.153 for long positions) Win rate exceeding 35% with balanced distribution across varied market conditions Institutional Considerations The strategy architecture addresses execution complexities faced by institutional participants with temporal filtering and date-range capabilities: // Time Filter settings with flexible timezone support import jason5480/time_filters/5 as time_filter src_timezone = input.string(defval = 'Exchange', title = 'Source Timezone') dst_timezone = input.string(defval = 'Exchange', title = 'Destination Timezone') // Date range filtering for precise execution windows use_from_date = input.bool(defval = true, title = 'Enable Start Date') from_date = input.time(defval = timestamp('01 Jan 2022 00:00'), title = 'Start Date') // Validate trading permission based on temporal constraints date_filter_approved = time_filter.is_in_date_range( use_from_date, from_date, use_to_date, to_date, src_timezone, dst_timezone ) These capabilities enable precise execution timing and market session optimization critical for larger market participants. Acknowledgments Special thanks to LuxAlgo for the pioneering work on trendline detection and breakout identification that inspired elements of this strategy. Their innovative approach to technical analysis provided a valuable foundation upon which I could build my Fibonacci-based methodology. This strategy is shared under the same Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license as LuxAlgo's original work. Past performance is not indicative of future results. Conduct thorough analysis before implementing any algorithmic strategy.

Strategi Pine Script®

oleh FibonacciFlux

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Volume Block Order Analyzer Core Concept The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements. How It Works: The Mathematical Model 1. Volume Anomaly Detection The strategy first identifies "block trades" using a statistical approach: ``` avgVolume = ta.sma(volume, lookbackPeriod) isHighVolume = volume > avgVolume * volumeThreshold ``` This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade. 2. Directional Impact Calculation For each block trade identified, its price action determines direction: - Bullish candle (close > open): Positive impact - Bearish candle (close < open): Negative impact The magnitude of impact is proportional to the volume size: ``` volumeWeight = volume / avgVolume // How many times larger than average blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10) ``` This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values. 3. Cumulative Impact with Time Decay The key innovation is the cumulative impact calculation with decay: ``` cumulativeImpact := cumulativeImpact * impactDecay + blockImpact ``` This mathematical model has important properties: - Recent block trades have stronger influence than older ones - Impact gradually "fades" at rate determined by decay factor (default 0.95) - Sustained directional pressure accumulates over time - Opposing pressure gradually counteracts previous momentum Trading Logic Signal Generation The strategy generates trading signals based on momentum shifts in institutional order flow: 1. Long Entry Signal: When cumulative impact crosses from negative to positive ``` if ta.crossover(cumulativeImpact, 0) strategy.entry("Long", strategy.long) ``` *Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement* 2. Short Entry Signal: When cumulative impact crosses from positive to negative ``` if ta.crossunder(cumulativeImpact, 0) strategy.entry("Short", strategy.short) ``` *Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement* 3. Exit Logic: Positions are closed when the cumulative impact moves against the position ``` if cumulativeImpact < 0 strategy.close("Long") ``` *Logic: The original signal is no longer valid as institutional flow has reversed* Visual Interpretation System The strategy employs multiple visualization techniques: 1. Color Gradient Bar System: - Deep green: Strong buying pressure (impact > 0.5) - Light green: Moderate buying pressure (0.1 < impact ≤ 0.5) - Yellow-green: Mild buying pressure (0 < impact ≤ 0.1) - Yellow: Neutral (impact = 0) - Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0) - Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1) - Red: Strong selling pressure (impact ≤ -0.5) 2. Dynamic Impact Line: - Plots the cumulative impact as a line - Line color shifts with impact value - Line movement shows momentum and trend strength 3. Block Trade Labels: - Marks significant block trades directly on the chart - Shows direction and volume amount - Helps identify key moments of institutional activity 4. Information Dashboard: - Current impact value and signal direction - Average volume benchmark - Count of significant block trades - Min/Max impact range Benefits and Use Cases This strategy provides several advantages: 1. Institutional Flow Detection: Identifies where large players are positioning themselves 2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements 3. Market Context Enhancement: Provides deeper insight than simple price action alone 4. Objective Decision Framework: Quantifies what might otherwise be subjective observations 5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds Customization Options The strategy allows users to fine-tune its behavior: - Volume Threshold: How unusual a volume spike must be to qualify - Lookback Period: How far back to measure average volume - Impact Decay Factor: How quickly older trades lose influence - Visual Settings: Labels and line width customization This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.

Strategi Pine Script®

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Scalper Bot [SMRT Algo]The SMRT Algo Bot is a trading strategy designed for use on TradingView, enabling traders to backtest and refine their strategies with precision. This bot is built to provide key performance metrics through TradingView’s strategy tester feature, offering insights such as net profit, maximum drawdown, profit factor, win rate, and more. The SMRT Algo Bot is versatile, allowing traders to execute either pro-trend or contrarian strategies, each with customizable parameters to suit individual trading styles. Traders can automate the bot to their brokerage platform via webhooks and use third-party software to facilitate this.  Core Features: Backtesting Capabilities: The SMRT Algo Bot leverages TradingView’s powerful strategy tester, allowing traders to backtest their strategies over historical data. This feature is crucial for assessing the viability of a strategy before deploying it in live markets. By providing metrics such as net profit, maximum drawdown, profit factor, and win rate, traders can gain a comprehensive understanding of their strategy's performance, helping them to make informed decisions about potential adjustments or optimizations. Advanced Take Profit and Stop Loss Methods: The SMRT Algo Bot offers multiple methods for setting Take Profit (TP) and Stop Loss (SL) levels, providing flexibility to match different market conditions and trading strategies. Take Profit Methods: - Normal (Percent-based): Traders can set their TP levels as a percentage. This method adjusts the TP dynamically based on market volatility, allowing for more responsive profit-taking in volatile markets. - Donchian Channel: Alternatively, the bot can use the Donchian Channel to set TP levels, which is particularly useful in trend-following strategies. The Donchian Channel identifies the highest high and lowest low over a specified period, providing a clear target for profit-taking when prices reach extreme levels. Stop Loss Methods: - Percentage-Based Stop Loss: This method allows traders to set a fixed percentage of the entry price as the stop loss. It provides a straightforward, static risk management approach that is easy to implement. - Normal (Percent-based): Traders can set their SL levels as a percentage. This method adjusts the SL dynamically based on market volatility, allowing for more responsive profit-taking in volatile markets. - ATR Multiplier: Similar to the TP method, the SL can also be set using a multiple of the ATR. Pro-Trend and Contrarian Strategies: The SMRT Algo Bot is designed to execute either pro-trend or contrarian trading strategies, though only one can be active at any given time. Pro-Trend Strategy: This strategy aligns with the prevailing market trend, aiming to capitalize on the continuation of current price movements. It is particularly effective in trending markets, where momentum is expected to carry the price further in the direction of the trend. Contrarian Strategy: In contrast, the contrarian strategy seeks to exploit potential reversals or corrections, trading against the prevailing trend. This approach is more suitable in overextended markets where a pullback is anticipated. Traders can switch between these strategies based on their market outlook and trading style. Dashboard Display: A dashboard located in the bottom right corner of the TradingView interface provides real-time updates on the bot’s performance metrics. This includes key statistics such as net profit, drawdown, profit factor, and win rate, specific to the current instrument being tested. This immediate access to performance data allows traders to quickly assess the effectiveness of the strategy and make necessary adjustments on the fly. Input Settings: Reverse Signals: If turned on, buy trades will be shown as sell trades, etc. Show Signal (Bar Color): Shows the signal bar as a green candle for buy or red candle for sell. RSI: Used as a filter for one of the conditions for trade. Can be turned on/off by clicking on the checkbox. Timeframe: Affects the timeframe of RSI filter. Length: Length of RSI used in measurement. First Cross: Whether or not to factor in the first RSI cross in the calculation. Buy/Sell (Above/Below): Look for trades if RSI is above or below these values. EMA: Used as a trend filter for one of the conditions for trade. Can be turned on/off by clicking on the checkbox. Timeframe: Affects the timeframe of EMA filter. Fast Length: Value for the fast EMA. Middle Length: Value for the middle EMA Slow Length: Value for the slow EMA. ADX: Used as a volatility filter for one of the conditions for trade. Can be turned on/off by clicking on the checkbox. Threshold: Threshold value for ADX. ADX Smoothing: Smoothing value for the ADX DI Length: DI length value for the ADX. Donchian Channel Length: This value affects the length value of the DC. Used in TP calculation. Close Trade On Opposite Signal: If true, the current trade will close if an opposite trade appears. RSI: If turned on, it will also use the RSI to exit the trade (overextended zones). Take Profit Option: Choose between normal (percentage-based) and Donchian Channel options. Stop Loss Option: Choose between normal (percentage-based) and Donchian Channel options. The SMRT Algo Bot’s components are designed to work together seamlessly, creating a comprehensive trading solution. Whether using the ATR multiplier for dynamic adjustments or the Donchian Channel for trend-based targets, these methods ensure that trades are managed effectively from entry to exit. The ability to switch between pro-trend and contrarian strategies offers adaptability, enabling traders to optimize their approach based on market behavior. The real-time dashboard ties everything together, providing continuous feedback that informs strategic adjustments. Unlike basic or open-source bots, which often lack the flexibility to adapt to different market conditions, the SMRT Algo Bot provides a robust and dynamic trading solution. The inclusion of multiple TP and SL methods, particularly the ATR and Donchian Channel, adds significant value by offering traders tools that can be finely tuned to both volatile and trending markets. The SMRT Algo Suite, which the SMRT Algo Bot is a part of, offers a comprehensive set of tools and features that extend beyond the capabilities of standard or open-source indicators, providing significant additional value to users. What you also get with the SMRT Algo Suite: Advanced Customization: Users can customize various aspects of the indicator, such as toggling the confirmation signals on or off and adjusting the parameters of the MA Filter. This customization enhances the adaptability of the tool to different trading styles and market conditions. Enhanced Market Understanding: The combination of pullback logic, dynamic S/R zones, and MA filtering offers traders a nuanced understanding of market dynamics, helping them make more informed trading decisions. Unique Features: The specific combination of pullback logic, dynamic S/R, and multi-level TP/SL management is unique to SMRT Algo, offering features that are not readily available in standard or open-source indicators. Educational and Support Resources: As with other tools in the SMRT Algo suite, this indicator comes with comprehensive educational resources and access to a supportive trading community, as well as 24/7 Discord support. The educational resources and community support included with SMRT Algo ensure that users can maximize the indicators’ potential, offering guidance on best practices and advanced usage. SMRT Algo believe that there is no magic indicator that is able to print money. Indicator toolkits provide value via their convenience, adaptability and uniqueness. Combining these items can help a trader make more educated; less messy, more planned trades and in turn hopefully help them succeed. RISK DISCLAIMER Trading involves significant risk, and most day traders lose money. All content, tools, scripts, articles, and educational materials provided by SMRT Algo are intended solely for informational and educational purposes. Past performance is not indicative of future results. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.

Strategi Pine Script®

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Friday Bond Short Strategy Strategy: Friday Bond Short Strategy (1H Timeframe) Objective: This strategy aims to open short positions on a specified day and hour (Eastern Time) and close those positions on another specified day and hour. The background color of the chart will turn green when a position is active, providing a visual cue of an open trade. Parameters: 1. Entry Day: • Defines the day of the week on which the short position will be opened. • Value: 6 for Friday (Pine Script’s weekday numbering: Monday = 2, Friday = 6). 2. Entry Hour: • Specifies the hour (Eastern Time) when the short position will be opened. • Value: 13 for 13:00 ET (1:00 PM). 3. Exit Day: • Defines the day of the week on which the short position will be closed. • Value: 2 for Monday. 4. Exit Hour: • Specifies the hour (Eastern Time) when the position will be closed. • Value: 13 for 13:00 ET (1:00 PM). How It Works: 1. Time Adjustment to Eastern Time: • The script converts all time references to Eastern Time (America/New_York) to ensure the strategy operates according to the desired time zone. 2. Entry Conditions: • The strategy checks if the current day of the week matches the specified entry_day and if the current hour matches the specified entry_hour. • If both conditions are met, a short position is opened (strategy.entry("Short", strategy.short)). 3. Exit Conditions: • Similarly, the strategy checks if the current day of the week matches the specified exit_day and if the current hour matches the specified exit_hour. • If both conditions are met, the open short position is closed (strategy.close("Short")). 4. Background Color: • The background color of the chart is adjusted based on whether there is an open position: • Green Background: If the strategy has an open position (strategy.position_size > 0), the background is set to light green. • No Background Color: If there is no open position, the background color is not set (na). Summary: The Friday Bond Short Strategy is designed to enter short positions on Fridays at 1:00 PM ET and close them on Mondays at 1:00 PM ET. The chart background color turns green when a short position is active, providing a clear visual indication of when the strategy is engaged in a trade.

Strategi Pine Script®

Supertrend Advance Pullback Strategy Handbook for the Supertrend Advance Strategy 1. Introduction Purpose of the Handbook: The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios. Overview of the Supertrend Advance Pullback Strategy: At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals. 1. Basic Concept: The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends. 2. Methodology: Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise. 3. Benefits: One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points. 4. Practical Applications: The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies. In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading. As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors. 2. Getting Started Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time. Setting up on TradingView: TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how: 1. Account Creation: • Visit TradingView's official website. • Click on the "Join for free" or "Sign up" button. • Follow the registration process, providing the necessary details and setting up your login credentials. 2. Navigating the Dashboard: • Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window. • To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top. 3. Configuring Chart Settings: • Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window. • Adjust the chart type, time intervals, and other display settings to your preference. Integrating the Strategy into a Chart: Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy. 1. Accessing the Pine Script Editor: • Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it. • This is where custom strategies and indicators are scripted or imported. 2. Loading the Supertrend Advance Strategy Script: • Depending on whether you have the script or need to find it, there are two paths: • If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor. • If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart. 3. Applying the Strategy: • After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window. 4. Configuring Strategy Settings: • Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings. • Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing. 5. Interpreting Signals: • With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions. 3. Strategy Overview What is the Supertrend Advance Strategy? The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals. In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point. Strategy Goals and Objectives: 1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor. 2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making. 3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability. 4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system. Type of Assets/Markets to Apply the Strategy: 1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices. 2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders. 3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements. 4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters. 5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits. It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades. 4. Input Settings Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance. Grouping Inputs: Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator. Strategy Choice: This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available. Supertrend Settings: 1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer. 2. Period: The number of bars used in the ATR calculation. A common default is 7. EMA Settings (Exponential Moving Average): 1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200. 2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation. RSI Settings (Relative Strength Index): 1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14. 2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70. 3. Oversold Level: The threshold at which the asset is considered oversold, often at 30. MACD Settings (Moving Average Convergence Divergence): 1. Short Period: The shorter EMA, usually set to 12. 2. Long Period: The longer EMA, commonly set to 26. 3. Signal Period: Defines the EMA of the MACD line, typically set at 9. CCI Settings (Commodity Channel Index): 1. Period: The number of bars used in the CCI calculation, often set to 20. 2. Overbought Level: Typically set at +100, denoting overbought conditions. 3. Oversold Level: Usually set at -100, indicating oversold conditions. SL/TP Settings (Stop Loss/Take Profit): 1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss. 2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit. Filtering Conditions: This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions. Trade Direction and Backtest Period: 1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both. 2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc. It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy. 5. Understanding Strategy Conditions Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point. Basic Logic Behind Conditions: Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future. Buy and Sell Conditions: 1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum. 2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum. Simple Strategy: The simple strategy could involve using just the Supertrend indicator. Here: • Buy: When price closes above the Supertrend line. • Sell: When price closes below the Supertrend line. Pullback Strategy: This strategy capitalizes on price retracements: • Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator. • Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator. Indicators Used: EMA (Exponential Moving Average): • Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish. RSI (Relative Strength Index): • Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold. MACD (Moving Average Convergence Divergence): • Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish. CCI (Commodity Channel Index): • Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition. And others... As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives. Logic Behind Each Indicator: 1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels. 2. RSI: Indicates overbought and oversold conditions based on recent price changes. 3. MACD: Showcases momentum and direction of a trend by comparing two EMAs. 4. CCI: Measures the difference between a security's price change and its average price change. Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets. 6. Trade Execution and Management Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy. Position Entry: Effective trade entry revolves around: 1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators. 2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal. 3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover. Position Exit Strategies: A successful exit strategy will lock in profits and minimize losses. Here are some strategies: 1. Fixed Time Exit: Exiting after a predetermined period. 2. Percentage-based Profit Target: Exiting after a certain percentage gain. 3. Indicator-based Exit: Exiting when an indicator gives an opposing signal. Percentage-based SL/TP: • Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses. • Example: A 2% SL on an entry at $100 would trigger a sell at $98. • Take Profit (TP): Set a fixed percentage above the entry price to lock in gains. • Example: A 5% TP on an entry at $100 would trigger a sell at $105. Supertrend-based SL/TP: • Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal. • Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum. Swing high/low-based SL/TP: • Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high. • Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support. And other methods... 1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor. 2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages. 3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal. Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance. 7. Visual Representations Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance. Understanding Plots on the Chart: Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves. 1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day. 2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves. Trend Lines: Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance: 1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal. 2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend. Filled Areas: These represent a range between two values on a chart, usually shaded or colored. For instance: 1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility. 2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels. Stop Loss and Take Profit Lines: These are horizontal lines representing pre-determined exit points for trades. 1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance. 2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors. Trailing Stop Lines: A trailing stop is a dynamic form of stop loss that moves with the price. On a chart: 1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in. 2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises. Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results. 8. Backtesting Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of. Setting Up Backtest Period: 1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years. 2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results. 3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments. Analyzing Backtest Results: 1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency. 2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics. 3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss. 4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover. 9. Tips and Best Practices Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy. When to Use the Strategy: 1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets. 2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news. 3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume. Adjusting Settings for Different Markets/Timeframes: 1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity. 2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes. 3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions. 10. Frequently Asked Questions (FAQs) Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy. 1. What exactly is the Supertrend Advance Strategy? The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals. 2. Can I use the Supertrend Advance Strategy for all asset types? Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type. 3. Is this strategy suitable for day trading? Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on. 4. How do I deal with false signals? No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals. 5. Do I need any prior trading experience to use this strategy? While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts. 6. How often should I review and adjust the strategy settings? There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments. 7. Can the Supertrend Advance Strategy be automated? Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended. 8. Are there any markets or conditions where the strategy shouldn't be used? The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market. 9. How important is backtesting with this strategy? Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades. 10. What if the strategy isn't working for me? No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success. Other comments Value of combining several indicators in this script and how they work together Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point. Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced. Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios. Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market. How do the different indicators in the Supertrend Advance Strategy work together? Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends. EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa. RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend. MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend. CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points. In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions. Backtesting and Default Settings • This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts. • This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security. • The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year. • Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security. • Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).

Strategi Pine Script®

oleh JS_TechTrading

[MT] Strategy Backtest Template | Initial Release | | EN | An update of my old script, this script is designed so that it can be used as a template for all those traders who want to save time when programming their strategy and backtesting it, having functions already programmed that in normal development would take you more time to program, with this template you can simply add your favorite indicator and thus be able to take advantage of all the functions that this template has. 🔴Stop Loss and 🟢Take Profit: No need to mention that it is a Stop Loss and a Take Profit, within these functions we find the options of: fixed percentage (%), fixed price ($), ATR, especially for Stop Loss we find the Pivot Points, in addition to this, the price range between the entry and the Stop Loss can be converted into a trailing stop loss, instead, especially for the Take Profit we have an option to choose a 1:X ratio that complements very well with the Pivot Points. 📈Heikin Ashi Based Entries: Heikin Ashi entries are trades that are calculated based on Heikin Ashi candles but their price is executed to Japanese candles, thus avoiding false results that occur in Heikin candlestick charts, this making in certain cases better results in strategies that are executed with this option compared to Japanese candlesticks. 📊Dashboard: A more visual and organized way to see the results and necessary data produced by our strategy, among them we can see the dates between which our operations are made regardless if you have activated some time filter, usual data such as Profit, Win Rate, Profit factor are also displayed in this panel, additionally data such as the total number of operations, how many were gains and how many losses, the average profit and loss for each operation and finally the maximum profits and losses followed, which are data that will be very useful to us when we elaborate our strategies. Feel free to use this template to program your own strategies, if you find errors or want to request a new feature let me know in the comments or through my social networks found in my tradingview profile. | Update 1.1 | | EN | ➕Additions: ' Time sessions filter and days of the week filter added to the time filter section. Option to add leverage to the strategy. 5 Moving Averages, RSI, Stochastic RSI, ADX, and Parabolic Sar have been added as indicators for the strategy. You can choose from the 6 available indicators the way to trade, entry alert or entry filter. Added the option of ATR for Take Profit. Ticker information and timeframe are now displayed on the dashboard. Added display customization and color customization of indicator plots. Added customization of display and color plots of trades displayed on chart. 📝Changes: Now when activating the time filter it is optional to add a start or end date and time, being able to only add a start date or only an end date. Operation plots have been changed from plot() to line creation with line.new(). Indicator plots can now be controlled from the "plots" section. Acceptable and deniable range of profit, winrate and profit factor can now be chosen from the "plots" section to be displayed on the dashboard. Aesthetic changes in the section separations within the settings section and within the code itself. The function that made the indicators give inputs based on heikin ashi candles has been changed, see the code for more information. ⚙️Fixes: Dashboard label now projects correctly on all timeframes including custom timeframes. Removed unnecessary lines and variables to take up less code space. All code in general has been optimized to avoid the use of variables, unnecessary lines and avoid unnecessary calculations, freeing up space to declare more variables and be able to use fewer lines of code. | Lanzamiento Inicial | | ES | Una actualización de mi antiguo script, este script está diseñado para que pueda ser usado como una plantilla para todos aquellos traders que quieran ahorrar tiempo al programar su estrategia y hacer un backtesting de ella, teniendo funciones ya programadas que en el desarrollo normal te tomaría más tiempo programar, con esta plantilla puedes simplemente agregar tu indicador favorito y así poder aprovechar todas las funciones que tiene esta plantilla. 🔴Stop Loss y 🟢Take Profit: No hace falta mencionar que es un Stop Loss y un Take Profit, dentro de estas funciones encontramos las opciones de: porcentaje fijo (%), precio fijo ($), ATR, en especial para Stop Loss encontramos los Pivot Points, adicionalmente a esto, el rango de precio entre la entrada y el Stop Loss se puede convertir en un trailing stop loss, en cambio, especialmente para el Take Profit tenemos una opción para elegir un ratio 1:X que se complementa muy bien con los Pivot Points. 📈Entradas Basadas en Heikin Ashi: Las entradas Heikin Ashi son operaciones que son calculados en base a las velas Heikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así́ los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas. 📊Panel de Control: Una manera más visual y organizada de ver los resultados y datos necesarios producidos por nuestra estrategia, entre ellos podemos ver las fechas entre las que se hacen nuestras operaciones independientemente si se tiene activado algún filtro de tiempo, datos usuales como el Profit, Win Rate, Profit factor también son mostrados en este panel, adicionalmente se agregaron datos como el número total de operaciones, cuantos fueron ganancias y cuantos perdidas, el promedio de ganancias y pérdidas por cada operación y por ultimo las máximas ganancias y pérdidas seguidas, que son datos que nos serán muy útiles al elaborar nuestras estrategias. Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mis redes sociales que se encuentran en mi perfil de tradingview. | Actualización 1.1 | | ES | ➕Añadidos: Filtro de sesiones de tiempo y filtro de días de la semana agregados al apartado de filtro de tiempo. Opción para agregar apalancamiento a la estrategia. 5 Moving Averages, RSI, Stochastic RSI, ADX, y Parabolic Sar se han agregado como indicadores para la estrategia. Puedes escoger entre los 6 indicadores disponibles la forma de operar, alerta de entrada o filtro de entrada. Añadido la opción de ATR para Take Profit. La información del ticker y la temporalidad ahora se muestran en el dashboard. Añadido personalización de visualización y color de los plots de indicadores. Añadido personalización de visualización y color de los plots de operaciones mostradas en grafica. 📝Cambios: Ahora al activar el filtro de tiempo es opcional añadir una fecha y hora de inicio o fin, pudiendo únicamente agregar una fecha de inicio o solamente una fecha de fin. Los plots de operaciones han cambiados de plot() a creación de líneas con line.new(). Los plots de indicadores ahora se pueden controlar desde el apartado "plots". Ahora se puede elegir el rango aceptable y negable de profit, winrate y profit factor desde el apartado "plots" para mostrarse en el dashboard. Cambios estéticos en las separaciones de secciones dentro del apartado de configuraciones y dentro del propio código. Se ha cambiado la función que hacía que los indicadores dieran entradas en base a velas heikin ashi, mire el código para más información. ⚙️Arreglos: El dashboard label ahora se proyecta correctamente en todas las temporalidades incluyendo las temporalidades personalizadas. Se han eliminado líneas y variables innecesarias para ocupar menos espacio en el código. Se ha optimizado todo el código en general para evitar el uso de variables, líneas innecesarias y evitar los cálculos innecesarios, liberando espacio para declarar más variables y poder utilizar menos líneas de código.

Strategi Pine Script®

BOCS Channel Scalper Strategy - Automated Mean Reversion System # BOCS Channel Scalper Strategy - Automated Mean Reversion System ## WHAT THIS STRATEGY DOES: This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range. ## KEY DIFFERENCE FROM ORIGINAL BOCS: **This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities: - **Original BOCS**: 1-3 signals per channel (only on breakout) - **Scalper Version**: 5-15+ signals per channel (every touch of entry zones) - **Trade Style**: Mean reversion vs trend following - **Hold Time**: Seconds to minutes vs minutes to hours - **Best Markets**: Ranging/choppy conditions vs trending breakouts This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management. ## TECHNICAL METHODOLOGY: ### Price Normalization Process: The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis. ### Volatility Detection: A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars). ### Channel Formation Logic: When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas. ### Entry Signal Generation: The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%): - **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2) - **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2) Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes. ### Cooldown Filter: An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period. ### ATR Volatility Filter: The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold: - If ATR ≥ threshold: Trading enabled - If ATR < threshold: No signals fire This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement. ### Take Profit Calculation: Two TP methods are available: **Fixed Points Mode**: - Long TP = Entry + (TP_Ticks × syminfo.mintick) - Short TP = Entry - (TP_Ticks × syminfo.mintick) **Channel Percentage Mode**: - Long TP = Entry + (ChannelRange × TP_Percent) - Short TP = Entry - (ChannelRange × TP_Percent) Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge. ### Stop Loss Placement: Stop losses are placed just outside the channel boundary by a user-defined tick offset: - Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick) - Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick) This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits. ### Trade Execution Logic: When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position): 1. Calculate entry price at zone boundary 2. Calculate TP and SL based on selected method 3. Execute strategy.entry() with calculated position size 4. Place strategy.exit() with TP limit and SL stop orders 5. Update info table with active trade details The strategy enforces one position at a time by checking strategy.position_size == 0 before entry. ### Channel Breakout Management: Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations. ### Position Sizing System: Three methods calculate position size: **Fixed Contracts**: - Uses exact contract quantity specified in settings - Best for futures traders (e.g., "trade 2 NQ contracts") **Percentage of Equity**: - position_size = (strategy.equity × equity_pct / 100) / close - Dynamically scales with account growth **Cash Amount**: - position_size = cash_amount / close - Maintains consistent dollar exposure regardless of price ## INPUT PARAMETERS: ### Position Sizing: - **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount - **Number of Contracts**: Fixed quantity per trade (1-1000) - **% of Equity**: Percentage of account to allocate (1-100%) - **Cash Amount**: Dollar value per position ($100+) ### Channel Settings: - **Nested Channels**: Allow multiple overlapping channels vs single channel - **Normalization Length**: Lookback for high/low calculation (1-500, default 100) - **Box Detection Length**: Period for volatility detection (1-100, default 14) ### Scalping Settings: - **Enable Long Scalps**: Toggle long entries on/off - **Enable Short Scalps**: Toggle short entries on/off - **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%) - **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5) - **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown) ### ATR Filter: - **Enable ATR Filter**: Toggle volatility filter on/off - **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.) - **ATR Length**: Smoothing period (1-100, default 14) - **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0) ### Take Profit Settings: - **TP Method**: Choose Fixed Points or % of Channel - **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30) - **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%) ### Appearance: - **Show Entry Zones**: Toggle zone labels on channels - **Show Info Table**: Display real-time strategy status - **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right) - **Color Settings**: Customize long/short/TP/SL colors ## VISUAL INDICATORS: - **Channel boxes** with semi-transparent fill showing consolidation zones - **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼" - **Entry signal arrows** below/above bars marking long/short entries - **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL) - **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status ## HOW TO USE: ### For 1-3 Minute Scalping (NQ/ES): - ATR Timeframe: "1" (1-minute) - ATR Min Value: 10.0 (for NQ), adjust per instrument - Entry Zone %: 20-25% - TP Method: Fixed Points, 20-40 ticks - SL Offset: 5-10 ticks - Cooldown: 2-3 bars - Position Size: 1-2 contracts ### For 5-15 Minute Day Trading: - ATR Timeframe: "5" or match chart - ATR Min Value: Adjust to instrument (test 8-15 for NQ) - Entry Zone %: 20-30% - TP Method: % of Channel, 40-60% - SL Offset: 5-10 ticks - Cooldown: 3-5 bars - Position Size: Fixed contracts or 5-10% equity ### For 30-60 Minute Swing Scalping: - ATR Timeframe: "15" or "30" - ATR Min Value: Lower threshold for broader market - Entry Zone %: 25-35% - TP Method: % of Channel, 50-70% - SL Offset: 10-15 ticks - Cooldown: 5+ bars or disable - Position Size: % of equity recommended ## BACKTEST CONSIDERATIONS: - Strategy performs best in ranging, mean-reverting markets - Strong trending markets produce more stop losses as price breaks channels - ATR filter significantly reduces trade count but improves quality during low volatility - Cooldown period trades signal quantity for signal quality - Commission and slippage materially impact sub-5-minute timeframe performance - Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions - % of Channel TP adapts better to varying channel sizes than fixed points - Fixed contract sizing recommended for consistent risk per trade in futures **Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability. ## COMPATIBLE MARKETS: Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality. ## KNOWN LIMITATIONS: - Immediate touch entry can fire multiple times in choppy zones without adequate cooldown - Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size - ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation) - Mean reversion logic fails in strong breakout scenarios leading to stop loss hits - Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price - No partial closing capability - full position exits at TP or SL only - Strategy does not account for gap openings or overnight holds ## RISK DISCLOSURE: Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively. ## ACKNOWLEDGMENT & CREDITS: This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community. Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.

Strategi Pine Script®

oleh TradeManager_PRO

Dow Theory Trend Strategy Dow Theory Trend Strategy (Pine Script) Overview This Pine Script implements a trading strategy based on the core principles of Dow Theory. It visually identifies trends (uptrend, downtrend) by analyzing pivot highs and lows and executes trades when the trend direction changes. This script is an improved version that features refined trend determination logic and strategy implementation. Core Concept: Dow Theory The script uses a fundamental Dow Theory concept for trend identification: Uptrend: Characterized by a series of Higher Highs (HH) and Higher Lows (HL). Downtrend: Characterized by a series of Lower Highs (LH) and Lower Lows (LL). How it Works Pivot Point Detection: It uses the built-in ta.pivothigh() and ta.pivotlow() functions to identify significant swing points (potential highs and lows) in the price action. The pivotLookback input determines the number of bars to the left and right required to confirm a pivot. Note that this introduces a natural lag (equal to pivotLookback bars) before a pivot is confirmed. Improved Trend Determination: The script stores the last two confirmed pivot highs and the last two confirmed pivot lows. An Uptrend (trendDirection = 1) is confirmed only when the latest pivot high is higher than the previous one (HH) AND the latest pivot low is higher than the previous one (HL). A Downtrend (trendDirection = -1) is confirmed only when the latest pivot high is lower than the previous one (LH) AND the latest pivot low is lower than the previous one (LL). Key Improvement: If neither a clear uptrend nor a clear downtrend is confirmed based on the latest pivots, the script maintains the previous trend state (trendDirection := trendDirection ). This differs from simpler implementations that might switch to a neutral/range state (e.g., trendDirection = 0) more frequently. This approach aims for smoother trend following, acknowledging that trends often persist through periods without immediate new HH/HL or LH/LL confirmations. Trend Change Detection: The script monitors changes in the trendDirection variable. changedToUp becomes true when the trend shifts to an Uptrend (from Downtrend or initial state). changedToDown becomes true when the trend shifts to a Downtrend (from Uptrend or initial state). Visualizations Background Color: The chart background is colored to reflect the currently identified trend: Blue: Uptrend (trendDirection == 1) Red: Downtrend (trendDirection == -1) Gray: Initial state or undetermined (trendDirection == 0) Pivot Points (Optional): Small triangles (shape.triangledown/shape.triangleup) can be displayed above pivot highs and below pivot lows if showPivotPoints is enabled. Trend Change Signals (Optional): Labels ("▲ UP" / "▼ DOWN") can be displayed when a trend change is confirmed (changedToUp / changedToDown) if showTrendChange is enabled. These visually mark the potential entry points for the strategy. Strategy Logic Entry Conditions: Enters a long position (strategy.long) using strategy.entry("L", ...) when changedToUp becomes true. Enters a short position (strategy.short) using strategy.entry("S", ...) when changedToDown becomes true. Position Management: The script uses strategy.entry(), which automatically handles position reversal. If the strategy is long and a short signal occurs, strategy.entry() will close the long position and open a new short one (and vice-versa). Inputs pivotLookback: The number of bars on each side to confirm a pivot high/low. Higher values mean pivots are confirmed later but may be more significant. showPivotPoints: Toggle visibility of pivot point markers. showTrendChange: Toggle visibility of the trend change labels ("▲ UP" / "▼ DOWN"). Key Improvements from Original Smoother Trend Logic: The trend state persists unless a confirmed reversal pattern (opposite HH/HL or LH/LL) occurs, reducing potential whipsaws in choppy markets compared to logic that frequently resets to neutral. Strategy Implementation: Converted from a pure indicator to a strategy capable of executing backtests and potentially live trades based on the Dow Theory trend changes. Disclaimer Dow Theory signals are inherently lagging due to the nature of pivot confirmation. The effectiveness of the strategy depends heavily on the market conditions and the chosen pivotLookback setting. This script serves as a basic template. Always perform thorough backtesting and implement proper risk management (e.g., stop-loss, take-profit, position sizing) before considering any live trading.

Strategi Pine Script®

oleh Salaryman_G

RSI + Stochastic + WMA Strategy This script is designed for TradingView and serves as a trading strategy (not just a visual indicator). It's intended for backtesting, strategy optimization, or live trading signal generation using a combination of popular technical indicators. 📊 Indicators Used in the Strategy: Indicator Description RSI (Relative Strength Index) Measures momentum; identifies overbought (>70) or oversold (<30) conditions. Stochastic Oscillator (%K & %D) Detects momentum reversal points via crossovers. Useful for timing entries. WMA (Weighted Moving Average) Identifies the trend direction (used as a trend filter). 📈 Trading Logic / Strategy Rules: 📌 Long Entry Condition (Buy Signal): All 3 conditions must be true: RSI is Oversold → RSI < 30 Stochastic Crossover Upward → %K crosses above %D Price is above WMA → Confirms uptrend direction 👉 Interpretation: Market was oversold, momentum is turning up, and price confirms uptrend — bullish entry. 📌 Short Entry Condition (Sell Signal): All 3 conditions must be true: RSI is Overbought → RSI > 70 Stochastic Crossover Downward → %K crosses below %D Price is below WMA → Confirms downtrend direction 👉 Interpretation: Market is overbought, momentum is turning down, and price confirms downtrend — bearish entry. 🔄 Strategy Execution (Backtesting Logic): The script uses: pinescript Copy Edit strategy.entry("LONG", strategy.long) strategy.entry("SHORT", strategy.short) These are Pine Script functions to place buy and sell orders automatically when the above conditions are met. This allows you to: Backtest the strategy Measure win/loss ratio, drawdown, and profitability Optimize indicator settings using TradingView Strategy Tester 📊 Visual Aids (Charts): Plots WMA Line: Orange line for trend direction Overbought/Oversold Zones: Horizontal lines at 70 (red) and 30 (green) for RSI visualization ⚡ Strategy Type Summary: Category Setting Strategy Type Momentum Reversal + Trend Filter Timeframe Flexible (Works best on 1H, 4H, Daily) Trading Style Swing/Intraday Risk Profile Medium to High (due to momentum triggers) Uses Leverage Possible (adjust risk accordingly)

Strategi Pine Script®

oleh RevoTheTrader

[3Commas] DCA Bot Tester DCA Bot Tester 🔷What it does: A tool designed to simulate the behavior of a Dollar Cost Averaging (DCA) strategy based on input signals from a source indicator. Additionally, it enables you to send activation signals to 3Commas Bots via TradingView webhooks. 🔷Who is it for: This tool is ideal for those who want a visual representation and strategy report of how a DCA Bot would perform under specific conditions. By adjusting the parameters, you can assess whether the strategy aligns with your risk/reward expectations before implementation, helping you save time and protect your capital. 🔷How does it work: The tool leverages a pyramiding function to simulate price averaging, mimicking how a DCA Bot operates. It calculates volume-based averaging and, upon reaching the target, closes the positions. Conversely, if the target isn't reached, a Stop Loss is triggered, potentially resulting in significant losses if improperly configured. 🔷Why It’s Unique Easy visualization of DCA Bot entry and exit points according to user preferences. DCA Bot Summary table same as the one shown in the new 3Commas interface. Use plots from other indicators as Entry Trigger Source, with a small modification of the code. Option to Review message format before sending Signals to 3Commas. Compatibility with Multi-Pair, and futures contract pairs. Option to filter signals by session and day according to the user’s timezone. 👉 Before continuing with the explanation of the tool, please take a few minutes to read this information, paying special attention to the risks of using DCA strategies. DCA Bot: What is it, how does it work, and what are its advantages and risks? A DCA Bot is an automated tool designed to simplify and optimize your trading operations, particularly in cryptocurrencies. Based on the concept of Dollar Cost Averaging (DCA) , this bot implements scaled strategies that allow you to distribute your investments intelligently. The key lies in dividing your capital into multiple orders, known as base orders and safety orders, which are executed at different price levels depending on market conditions. These bots are highly customizable, meaning you can adapt them to your goals and trading style, whether you're operating Long (expecting a price increase) or Short (expecting a price decrease). Their primary purpose is to reduce the impact of entries that move against the estimated direction and ensure you achieve a more favorable average price. 🔸 Key Features of DCA Bots Customizable configuration: DCA bots allow you to adjust the size of your initial investment, the number of safety orders, and the price levels at which these orders execute. These orders can be equal or incremental, depending on your risk tolerance. Scaled safety orders: If the asset's price moves against your position, the bot executes safety orders at strategic levels to average your entry price and increase your chances of closing in profit. Automatic Take Profit: When the predefined profit level is reached, the bot closes the position, ensuring net gains by averaging all entries made using the DCA strategy. Stop Loss option: To protect your capital, you can set a stop loss level that limits losses if the market moves drastically against your position. Flexibility: Bots can integrate with 3Commas technical indicators or external signals from TradingView, allowing you to trade in any trend, whether bullish or bearish. Support for multiple assets: You can trade cryptocurrency pairs and exchanges compatible with 3Commas, offering a wide range of possibilities to diversify your strategies. ✅ Advantages of DCA Bots Time-saving automation: DCA bots eliminate the need for constant market monitoring, executing your trades automatically and efficiently based on predefined settings. Favorable averages in volatile markets: By averaging your entries, the bot can offer more competitive prices even under adverse market conditions. This increases your chances of recovering a position and closing it profitably. Advanced capital management: With customizable settings, you can adjust the size of base and safety orders to optimize capital usage and reduce risk. Additional protection: The ability to set a stop loss ensures your losses are limited, safeguarding your capital in extreme scenarios. ⚠️ Risks of Using a DCA Bot Requires significant capital: Safety orders can accumulate quickly if the price moves against your position. This issue is compounded if increasing amounts are used for safety orders, which can immobilize large portions of capital in adverse markets. Markets lacking clear direction: During consolidation periods or erratic movements, the bot may generate unrealized losses and make position recovery difficult. Opportunity cost: Investing in an asset that doesn't show favorable behavior can prevent you from seizing opportunities in other markets. Emotional pressure: Large investments in advanced stages of the DCA strategy can cause stress, especially if an asset takes too long to reach your take profit level. Dependence on market recovery: DCA assumes that the price will eventually move in your favor, which does not always happen, especially in assets without solid fundamentals. 📖 Key Considerations for Effectively Using a DCA Bot Use small amounts for your base and safety orders: Setting small initial orders not only limits capital usage but also allows you to manage multiple bots simultaneously, maximizing portfolio diversification. Capital management: Define a clear budget and never risk more than you are willing to lose. This is essential for maintaining sustainable operations. Select assets with strong fundamentals: Apply DCA to assets you understand and that have solid fundamentals and a proven historical growth record. Additionally, analyze each cryptocurrency's fundamentals: What problem does it solve? Does it have a clear use case? Is it viable in the long term? These questions will help you make more informed decisions. Diversification: Do not concentrate all your capital on a single asset or strategy. Spread your risk across multiple bots or assets. Monitor regularly: While bots are automated and eliminate the need to monitor the market constantly, it is essential to monitor the bots themselves to ensure they are performing as expected. This includes reviewing their performance and making adjustments if market conditions change. Remember, the goal is to automate trades, but active bot management is crucial to avoid surprises. A DCA Bot is a powerful tool for traders looking to automate their strategies and reduce the impact of market fluctuations. However, like any tool, its success depends on how it is configured and used. By applying solid capital management principles, carefully selecting assets, and using small amounts in your orders, you can maximize its potential and minimize risks. 🔷FEATURES & HOW TO USE 🔸Strategy: Here you must select the type of signal you are going to analyze and send signals to the DCA Bot, either Long for buy signals or Short for sell signals. This must match the Bot created in 3Commas. 🔸Add a Source Indicator for Entry Triggers Tradingview allows us to use indicator plots as a source in other indicators, we will use this functionality so that the buy or sell signals of an indicator are processed by the DCA Bot Tester. In this EXAMPLE we will use a simple strategy that uses a Donchian Channel (DC) and an Exponential Moving Average (EMA). Trigger to buy or long signal will be when: the price closes above the previous upper level and the average of the upper and lower level (basis) is greater than the EMA. Trigger sell or short signal will be when: the price closes below the previous lower level and the average of the upper and lower level (basis) is less than the EMA. trigger_buy = ta.crossover (close,upper ) and basis > ema and barstate.isconfirmed trigger_sell = ta.crossunder(close,lower ) and basis < ema and barstate.isconfirmed Then we create the plots that will be used as input source in the DCA Bot Tester indicator. When a buy condition is given the plot "🟢 Trigger Buy" will have a value of 1 otherwise it will remain at 0. When a sell condition is given the plot "🔴 Trigger Sell" will have a value of -1 otherwise it will remain at 0. plot(trigger_buy ? 1 : 0 , '🟢 Trigger Buy' , color = na, display = display.data_window) plot(trigger_sell? -1 : 0 , '🔴 Trigger Sell', color = na, display = display.data_window) Here you have the complete code so you can use it and do tests. Basically you just have to define the buy or sell conditions of your preferred indicator or strategy and then create the plots with the same format that will be used in DCA Bot Tester. //@version=6 indicator(title="Simple Strategy Example", overlay= false) // Indicator and Signal Triggers length = input.int(10, title = "DC Length" , display = display.none) length_ema = input.int(50, title = "EMA Length", display = display.none) lower = ta.lowest (length) upper = ta.highest(length) ema = ta.ema (close, length_ema) basis = math.avg (upper, lower) plot(basis, "Basis", color = color.orange, display = display.all-display.status_line) plot(upper, "Upper", color = color.blue , display = display.all-display.status_line) plot(lower, "Lower", color = color.blue , display = display.all-display.status_line) plot(ema , "EMA" , color = color.red , display = display.all-display.status_line) candlecol = open < close ? color.teal : color.red plotcandle(open, high, low, close, title='Candles', color = candlecol, wickcolor = candlecol, bordercolor = candlecol, display = display.pane) trigger_buy = ta.crossover (close,upper ) and basis > ema and barstate.isconfirmed trigger_sell = ta.crossunder(close,lower ) and basis < ema and barstate.isconfirmed plotshape(trigger_buy ?close:na, title="Label Buy" , style=shape.labelup , location= location.belowbar, color=color.green, text="B", textcolor=color.white, display=display.pane) plotshape(trigger_sell?close:na, title="Label Sell", style=shape.labeldown, location= location.abovebar, color=color.red , text="S", textcolor=color.white, display=display.pane) // ―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――― // 👇 Plots to be used in the DCA Bot Indicator as source triggers. // ―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――― plot(trigger_buy ? 1 : 0 , '🟢 Trigger Buy' , color = na, display = display.data_window) plot(trigger_sell? -1 : 0 , '🔴 Trigger Sell', color = na, display = display.data_window) To use the example code Open the Pine Editor, paste the code and then click Add to chart. Then in the Plot Entry Trigger Source option, we will select 🟢 Trigger Buy, as the plot that will give us the buy signals when it is worth 1, otherwise for the sell signals you must change the value to -1 in the Plot Entry Trigger Value and remember to change the strategy mode to Short. 🔸DCA Settings: Here you need to configure the DCA values of the strategy, you can see the meaning of each value in the Settings Section. Once you are satisfied with the tests configure the 3Commas DCA Bot with the same values so that the Summary Table matches the 3Commas Table. Pay close attention to the Total Volume that the Bot will use, according to the amount of Safety Orders you are going to execute, and that all the values in the table adapt to your risk tolerance. 🔸DCA Bot Deal Start: Once you create the Bot in 3Commas with the same settings it will give you a Deal Start Message, you must copy and paste it in this section, verify that it is the same in the summary table, this is used to be sent through tradingview alerts to the Bot and it can process the signals. 🔸DCA Bot Multi-Pair: A Multi-Pair Bot allows you to manage several pairs with a single bot, but you must specify which pair it will run on. You must activate it if you want to use the signals in a DCA Bot Multi-pair. In the text box you must enter (using the 3Commas format) the symbol for each pair before you create the alert so that the bot understands which pair to work on. In the following image we would be configuring the indicator to send a signal to activate the bot in the BTCUSDT pair using the given format it would be USDT_BTC, but if we wanted to send a signal in another pair we must change the pair in the chart and also in the configuration, an example with ETHUSDT would be USDT_ETH. After this we could create the alert, and the Mult-Pair Bot would detect it correctly. 🔸Strategy Tester Filters: This is useful if you want to test the strategy's result on a certain time window, the indicator will only enter this range. If disabled it will use all historical data available on the chart. If you are going to use the tool to send signals, make sure to disable the Use Custom Test Period. If you want the entries to only run at a certain time and day, in that case make sure that the timezone matches the one you are using in the chart. 🔸Properties: Adjust your initial capital and exchange commission appropriately to achieve realistic results. 🔸Create alerts to trigger the DCA Bot Check that the message is the same as the one indicated by the DCA Bot. In the case of Multi-Pair, enable the option to add the symbol with the correct format. When creating an alert, select Any alert() function call. Enter the any name of the alert. Open the Notifications tab and enable Webhook URL Paste Webhook URL provided by 3Commas looking in the section How to use TradingView custom signals. Done, alerts will be sent with the correct format automatically to 3Commas. 🔷 INDICATOR SETTINGS 🔸3Commas DCA Bot Settings Strategy: Select the direction of the strategy to test Long or Short, this must be the same as the Bot created in 3Commas, so that the signals are processed properly. DCA Bot Deal Start: Copy and paste the message for the deal start signal of the DCA Bot you created in 3Commas. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the 3Commas bot so that it can process properly so that it executes and starts the trade. DCA Bot Multi-Pair: A Multi-Pair Bot allows you to manage several pairs with a single bot, but you must specify which pair it will run on. DCA Bot Summary Table: Here you can activate the display of table as well as change the size, position, text color and background color. 🔸Source Indicator Settings Plot Entry Trigger Source: Select a Plot for Entries of the Source Indicator. This refers to the Long or Short entry signal that the indicator will use as BO (Base Order). Plot Entry Trigger Value: Value of the Source Indicator to Deal Start Condition Trigger. The default value is 1, this means that when a signal is given for example Long in the source indicator, we will use 1 or for Short -1 if there is no signal it will be 0 so it will not execute any entry, please review the example code and adjust the indicator you are going to use in the same way. 🔸DCA Settings Base Order: The Base Order is the first order the bot will create when starting a new deal. Safety Order: Enter the amount of funds your safety orders will use to average the cost of the asset being traded.Safety orders are also known as Dollar Cost Averaging and help when prices move in the opposite direction to your bot's take profit target. Safety Orders Deviation %: Enter the percentage difference in price to create the first Safety Order. All Safety Orders are calculated from the price the initial Base Order was filled on the exchange account. Safety Orders Max Count: This is the total number of Safety Orders the bot is allowed to use per deal that is opened. All Safety Orders created by the bot are placed as Limit Orders on the exchange's order book. Safety Orders Volume Scale: The Safety Order Volume Scale is used to multiply the amount of funds used by the last Safety Order that was created. Using a larger amount of funds for Safety Orders allows your bot to be more aggressive at Dollar Cost Averaging the price of the asset being traded. Safety Orders Step Scale: The Safety Order Step Scale is used to multiply the Price Deviation percentage used by the last Safety Order placed on the exchange account. Using a larger value here will reduce the amount of Safety Orders your bot will require to cover a larger move in price in the opposite direction to the active deal's take profit target. Take Profit %: The Take Profit section offers tools for flexible management of target parameters: automatic profit upon reaching one or more target levels in percentage. Stop Loss % | Use SL: To enable Stop Loss, please check the "Use SL" box. This is the percentage that price needs to move in the opposite direction to close the deal at a loss. This must be greater than the sum of the deviations from the safety orders. 🔸Strategy Tester Filters Use Custom Test Period: When enabled signals only works in the selected time window.. If disabled it will use all historical data available on the chart. Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze. Session Filter | Days | Background: Here you can choose a time zone in which signals will be sent or your strategy will be tested, as well as the days and a background of it. It is important that you use the same timezone as your chart so that it matches. 👨🏻‍💻💭 If this tool helps you, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions. _________________________________________________________________ The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.

Strategi Pine Script®

AlgoBuilder [Mean-Reversion] | Fractalyst What's the strategy's purpose and functionality? This strategy is designed for both traders and investors looking to rely and trade based on historical and backtested data using automation. The main goal is to build profitable mean-reversion strategies that outperform the underlying asset in terms of returns while minimizing drawdown. For example, as for a benchmark, if the S&P 500 (SPX) has achieved an estimated 10% annual return with a maximum drawdown of -57% over the past 20 years, using this strategy with different entry and exit techniques, users can potentially seek ways to achieve a higher Compound Annual Growth Rate (CAGR) while maintaining a lower maximum drawdown. Although the strategy can be applied to all markets and timeframes, it is most effective on stocks, indices, future markets, cryptocurrencies, and commodities and JPY currency pairs given their trending behaviors. In trending market conditions, the strategy employs a combination of moving averages and diverse entry models to identify and capitalize on upward market movements. It integrates market structure-based moving averages and bands mechanisms across different timeframes and provides exit techniques, including percentage-based and risk-reward (RR) based take profit levels. Additionally, the strategy has also a feature that includes a built-in probability function for traders who want to implement probabilities right into their trading strategies. Performance summary, weekly, and monthly tables enable quick visualization of performance metrics like net profit, maximum drawdown, profit factor, average trade, average risk-reward ratio (RR), and more. This aids optimization to meet specific goals and risk tolerance levels effectively. ----- How does the strategy perform for both investors and traders? The strategy has two main modes, tailored for different market participants: Traders and Investors. Trading: 1. Trading: - Designed for traders looking to capitalize on bullish trending markets. - Utilizes a percentage risk per trade to manage risk and optimize returns. - Suitable for active trading with a focus on mean-reversion and risk per trade approach. ◓: Mode | %: Risk percentage per trade 3. Investing: - Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown. - Utilizes pre-define percentage of the equity to buy, hold, and manage the asset. - Focuses on long-term growth and capital appreciation by fully investing in the asset during bullish conditions. - ◓: Mode | %: Risk not applied (In investing mode, the strategy uses 10% of equity to buy the asset) ----- What's is FRMA? How does the triple bands work? What are the underlying calculations? Middle Band (FRMA): The middle band is the core of the FRMA system. It represents the Fractalyst Moving Average, calculated by identifying the most recent external swing highs and lows in the market structure. By determining these external swing pivot points, which act as significant highs and lows within the market range, the FRMA provides a unique moving average that adapts to market structure changes. Upper Band: The upper band shows the average price of the most recent external swing highs. External swing highs are identified as the highest points between pivot points in the market structure. This band helps traders identify potential overbought conditions when prices approach or exceed this upper band. Lower Band: The lower band shows the average price of the most recent external swing lows. External swing lows are identified as the lowest points between pivot points in the market structure. The script utilizes this band to identify potential oversold conditions, triggering entry signals as prices approach or drop below the lower band. Adjustments Based on User Inputs: Users can adjust how the upper and lower bands are calculated based on their preferences: Upper/Lower: This method calculates the average bands using the prices of external swing highs and lows identified in the market. Percentage Deviation from FRMA: Alternatively, users can opt to calculate the bands based on a percentage deviation from the middle FRMA. This approach provides flexibility to adjust the width of the bands relative to market conditions and volatility. ----- What's the purpose of using moving averages in this strategy? What are the underlying calculations? Using moving averages is a widely-used technique to trade with the trend. The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages. The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns. By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades. The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition. This comparison filter can be turned on (>) or off. For example, you can set the filter so that MA#1 > MA#2, meaning the first moving average must be above the second one before the script looks for entry conditions. This adds an extra layer of trend confirmation, ensuring that trades are only taken in more favorable market conditions. ⍺: MA Period | Σ: MA Timeframe ----- What entry modes are used in this strategy? What are the underlying calculations? The strategy by default uses two different techniques for the entry criteria with user-adjustable left and right bars: Breakout and Fractal. 1. Breakout Entries : - The strategy looks for pivot high points with a default period of 3. - It stores the most recent high level in a variable. - When the price crosses above this most recent level, the strategy checks if all conditions are met and the bar is closed before taking the buy entry. ◧: Pivot high left bars period | ◨: Pivot high right bars period 2. Fractal Entries : - The strategy looks for pivot low points with a default period of 3. - When a pivot low is detected, the strategy checks if all conditions are met and the bar is closed before taking the buy entry. ◧: Pivot low left bars period | ◨: Pivot low right bars period 2. Hunt Entries : - The strategy identifies a candle that wicks through the lower FRMA band. - It waits for the next candle to close above the low of the wick candle. - When this condition is met and the bar is closed, the strategy takes the buy entry. By utilizing these entry modes, the strategy aims to capitalize on bullish price movements while ensuring that the necessary conditions are met to validate the entry points. ----- What type of stop-loss identification method are used in this strategy? What are the underlying calculations? Initial Stop-Loss: 1. ATR Based: The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves. Calculation: - To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close. The True Range is the largest of the following: - Current Period High minus Current Period Low - Absolute Value of Current Period High minus Previous Period Close - Absolute Value of Current Period Low minus Previous Period Close - The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14). Example - ATR (14) * 2 ⍺: ATR period | Σ: ATR Multiplier 2. ADR Based: The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days. Calculation: - To calculate the ADR for a particular day: - Calculate the average of the high prices over a specified number of days. - Calculate the average of the low prices over the same number of days. - Find the difference between these average values. - The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements. Example - ADR (20) * 2 ⍺: ADR period | Σ: ADR Multiplier 3. PL Based: This method places the stop-loss at the low of the previous candle. If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band. Example: If the previous candle's low is 100, then the stop-loss will be set at 100. This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management. Application in Strategy (ATR/ADR): - The strategy calculates the current bar's ADR/ATR with a user-defined period. - It then multiplies the ADR/ATR by a user-defined multiplier to determine the initial stop-loss level. By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. ----- What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations? For Break-Even: Percentage (%) Based: Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry. Calculation: Break-even level = Entry Price * (1 + Percentage / 100) Example: If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105. Risk-to-Reward (RR) Based: Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio. Calculation: Break-even level = Entry Price + (Initial Risk * RR Ratio) Example: If the entry price is $100, the initial risk is $10, and the RR ratio is 2, the break-even level is $100 + ($10 * 2) = $120. FRMA Based: Moves the stop-loss to break-even when the price hits the FRMA level at which the entry was taken. Calculation: Break-even level = FRMA level at the entry Example: If the FRMA level at entry is $102, the break-even level is set to $102 when the price reaches $102. For TP1 (Take Profit 1): - You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled. - Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR. For TP2 (Take Profit 2): - You can choose to set a take profit level at which your position gets fully closed. - As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR. When Both Percentage (%) Based and RR Based Take Profit Levels Are Off: The script will adjust the take profit level to the higher FRMA band set within user inputs. Calculation: Take profit level = Higher FRMA band length/timeframe specified by the user. This ensures that when neither percentage-based nor risk-to-reward-based take profit methods are enabled, the strategy defaults to using the higher FRMA band as the take profit level, providing a consistent and structured approach to profit-taking. For TP1 and TP2, it's specifying the price levels at which the position is partially or fully closed based on the chosen method (percentage or RR) above the entry price. These calculations are crucial for managing risk and optimizing profitability in the strategy. ⍺: BE/TP type (%/RR) | Σ: how many RR/% above the current price ----- What's the ADR filter? What does it do? What are the underlying calculations? The Average Day Range (ADR) measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days. The period of the ADR filter used in this strategy is tied to the same period you've used for your initial stop-loss. Users can define the minimum ADR they want to be met before the script looks for entry conditions. ADR Bias Filter: - Compares the current bar ADR with the ADR (Defined by user): - If the current ADR is higher, it indicates that volatility has increased compared to ADR (DbU).(⬆) - If the current ADR is lower, it indicates that volatility has decreased compared to ADR (DbU).(⬇) Calculations: 1. Calculate ADR: - Average the high prices over the specified period. - Average the low prices over the same period. - Find the difference between these average values in %. 2. Current ADR vs. ADR (DbU): - Calculate the ADR for the current bar. - Calculate the ADR (DbU). - Compare the two values to determine if volatility has increased or decreased. By using the ADR filter, the strategy ensures that trades are only taken in favorable market conditions where volatility meets the user's defined threshold, thus optimizing entry conditions and potentially improving the overall performance of the strategy. >: Minimum required ADR for entry | %: Current ADR comparison to ADR of 14 days ago. ----- What's the probability filter? What are the underlying calculations? The probability filter is designed to enhance trade entries by using buyside liquidity and probability analysis to filter out unfavorable conditions. This filter helps in identifying optimal entry points where the likelihood of a profitable trade is higher. Calculations: 1. Understanding Swing highs and Swing Lows Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right. Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right. 2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels. 3. Understanding probability calculations 1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive 2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active 3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences. 5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities. Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity. Example - BSL > 55% ----- What's the range length Filter? What are the underlying calculations? The range length filter identifies the price distance between buyside and sellside liquidity levels in percentage terms. When enabled, the script only looks for entries when the minimum range length is met. This helps ensure that trades are taken in markets with sufficient price movement. Calculations: Range Length (%) = ( ( Buyside Level − Sellside Level ) / Current Price ) ×100 Range Bias Identification: Bullish Bias: The current range price has broken above the previous external swing high. Bearish Bias: The current range price has broken below the previous external swing low. Example - Range length filter is enabled | Range must be above 1% >: Minimum required range length for entry | %: Current range length percentage in a (Bullish/Bearish) range ----- What's the day filter Filter, what does it do? The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style. Customize Session Time: Users can define the start and end times for the trading session. This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours. Select Days: Users can select which days of the week to include in the strategy. This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays). Benefits: Focus on Optimal Trading Periods: By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities. Avoid Unfavorable Conditions: Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays. Increased Flexibility: The filter provides increased flexibility, allowing traders to adapt the strategy to their specific needs and preferences. Example - Day filter | Session Filter θ: Session time | Exchange time-zone ----- What tables are available in this script? Table Type: - Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more. Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit. MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position. Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses. Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit. Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control. BE Trades: Number of break-even trades, excluding commission/slippage. Losing Trades: The total number of losing trades generated by the strategy. Winning Trades: The total number of winning trades generated by the strategy. Total Trades: Total number of taken traders visible your charts. Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign. - Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month. - Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations. - OFF: Hides the performance table. Profit Color: - Allows users to set the color for representing profit in the performance table, helping to quickly distinguish profitable periods. Loss Color: - Allows users to set the color for representing loss in the performance table, helping to quickly identify loss-making periods. These customizable tables provide traders with flexible and detailed performance analysis, aiding in better strategy evaluation and optimization. ----- User-input styles and customizations: To facilitate studying historical data, all conditions and rules can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions. Please note that all background colors in the style are disabled by default to enhance visualization. ----- How to Use This Algobuilder to Create a Profitable Edge and System: Choose Your Strategy mode: - Decide whether you are creating an investing strategy or a trading strategy. Select a Market: - Choose a one-sided market such as stocks, indices, or cryptocurrencies. Historical Data: - Ensure the historical data covers at least 10 years of price action for robust backtesting. Timeframe Selection: - Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits. Set Commission and Slippage: - Properly set the commission and slippage in the strategy properties according to your broker or prop firm specifications. Parameter Optimization: - Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester. Trade Count: - Ensure the number of trades is 100 or more; the higher, the better for statistical significance. Positive Average Trade: - Make sure the average trade value is above zero. (An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.) Performance Metrics: - Look for a high profit factor, and net profit with minimum drawdown. - Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance. Refinement and Optimization: - Try out different markets and timeframes. - Continue working on refining your edge using the available filters and components to further optimize your strategy. Automation: - Once you’re confident in your strategy, you can use the automation section to connect the algorithm to your broker or prop firm. - Trade a fully automated and backtested trading strategy, allowing for hands-free execution and management. ----- What makes this strategy original? 1. Incorporating direct integration of probabilities into the strategy. 2. Utilizing built-in market structure-based moving averages across various timeframes. 4. Offering both investing and trading strategies, facilitating optimization from different perspectives. 5. Automation for efficient execution. 6. Providing a summary table for instant access to key parameters of the strategy. ----- How to use automation? For Traders: 1. Ensure the strategy parameters are properly set based on your optimized parameters. 2. Enter your PineConnector License ID in the designated field. 3. Specify the desired risk level. 4. Provide the Metatrader symbol. 5. Check for chart updates to ensure the automation table appears on the top right corner, displaying your License ID, risk, and symbol. 6. Set up an alert with the strategy selected as Condition and the Message as {{strategy.order.alert_message}}. 7. Activate the Webhook URL in the Notifications section, setting it as the official PineConnector webhook address. 8. Double-check all settings on PineConnector to ensure the connection is successful. 9. Create the alert for entry/exit automation. For Investors: 1. Ensure the strategy parameters are properly set based on your optimized parameters. 2. Choose "Investing" in the user-input settings. 3. Create an alert with a specified name. 4. Customize the notifications tab to receive alerts via email. 5. Buying/selling alerts will be triggered instantly upon entry or exit order execution. ----- Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited. By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.

Strategi Pine Script®

oleh Fractalyst

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