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Easy Trade Pro [Buy and Sell Strategy + Backtesting System]Hello Traders, Easy Trade Pro is a comprehensive tool that combines multiple technical indicators into a single customizable one. This tool is the culmination of an extensive trading career, it is designed to help traders navigate the markets in any timeframe and financial asset, like Equities, Futures, Crypto, Forex and Commodities. Before we deep dive into the comprehensive guide on what Easy Trade Pro is, let's kick off by showcasing the strategy used in this example. Please note, we have adopted an extremely conservative approach strictly following the Tradingview House Rules, which you can review here: www.tradingview.com The backtest strategy parameters: Currency pair: EUR USD Timeframe: 15-min chart Market: Spot, no leverage Broker: FXCM Trading range: 2022-09-01 07:30 — 2023-06-26 20:00 Backtesting range: 2022-08-31 23:00 — 2023-06-26 20:00 Initial Capital: $10,000 Buy Order Size: 20% of the capital, $2,000 Stop Loss: 0.50% Sell orders: Four different take profits where we unload the position by 25% each time Broker Fees: Commission set at 0.08$ Slippage: 10 ticks Understanding FXCM Commissions and Setting Realistic Slippage for EUR/USD Spot Trading: ◉I would like to provide some clarity on the commission structure and slippage setting used in the study for trading the EUR/USD pair on the FXCM spot market. Based on the information available, FXCM charges a commission of $4.00 per standard lot (100,000) on both sides of the trade (meaning at open and close) for the EUR/USD pair. Since the study involve an order size of $2,000 USD, which is equivalent to 0.02 lots, the commission fee for one side of the trade (either buying or selling) would be calculated as $4.00 multiplied by 0.02, which is $0.08. This means that for each individual trade, whether it be a buy or sell, the commission fee would be $0.08. ◉As for slippage, it is crucial to account for the inherent uncertainty in the execution price due to market fluctuations. In the forex market, the EUR/USD pair is quoted with a precision of five decimal places, with the smallest price change being a "pipette" (0.00001). Given that slippage can vary based on market conditions, it is considered fair practice to use a slippage of around 10 ticks under normal market conditions for the EUR/USD pair. This allows for a more realistic representation of the execution price, especially in a liquid and fast-moving market such as forex. More detailed information about FXCM fees structure in the link below: docs.fxcorporate.com Enter a Trade conditions: For our buy order, we utilize a custom buy signal called 'Bullish Reversal'. A detailed explanation of this and other buy orders can be found later in the guide, specifically in section 1). To enhance realism in our trading strategy, we have implemented a confirmation mechanism. When utilizing the strategy tester, you have the option to input a value to determine the number of confirmation candles to consider. For example, if you set the input to 1, the system will check if the next candle following the signal meets the criteria for confirmation. If set to 2, the system will evaluate the second candle, and so on for higher values. The confirmation is determined by comparing the closing or opening price of the selected buy signal candle with the corresponding closing price of the confirmation candle. In this case we choose as buy signal: 'Bullish Reversal' + 2 candle of confirmation Exit a trade conditions: On the sell side, we exit a trade in four different types of sell orders where we take profits. Inside '', you will encounter unique labels attributed to our custom sell signals. A detailed explanation of these sell orders can be found later in the guide, specifically in section 1). We used custom order called: 1TP 'Good Sell' 2TP 'Good Sell' 3TP 'Good Sell' 4TP 'Bearish Reversal' + 4 confirmation candles Our confirmation logic, for sell signals, is applied only to 'Bearish Reversal' signal. The confirmation is determined by comparing the closing or opening price of the selected 'Bearish Reversal' candle with the corresponding closing price of the confirmation candle. In this case, we wait for the fourth candle from the 'Bearish Reversal' signal to confirm the sell trade. Protect your capital: This super-conservative study involves a clear low risk, with the use of $2,000, 20% of our capital. If the stop loss of 0.5% were triggered, we lose 10$, equating to 0.10% of $10,000 - thus affecting only 0.10% of our capital. Super Conservative Approach & Results: With 353 closed trades, we achieved a net profit of 2.03%, or $203.34$ relative to our initial $10,000 capital, and a win rate of 73.37%. Less Conservative Approach & Results: We could also consider increasing our risk to 0.5% of our capital per trade. We would maintain our stop loss at 0.50%, but we would need to use all our capital to enter the market. If the stop loss of 0.5% will be triggered, we would lose 50$, equating to 0.5% of $10,000. In this scenario, our net profit would have increased to 10.15%, equivalent to $1015. Please be aware: While fully automated strategies can bring considerable advantages, they are not without their cons. For one, relying solely on an automated system may not take into account the potential confluence of other strategies or indicators, such as the significance of support and resistance zones. These elements often require a more nuanced, human understanding of the markets and cannot always be perfectly replicated by an algorithm. Additionally, it's essential to remember that a significant percentage of traders are not consistently profitable. As such, prudent risk management, a conservative approach, and acceptance of a reasonable profit are crucial aspects of successful trading. While the allure of high returns can be tempting, the sustainability of your trading strategy should always take precedence. Achieving steady, reliable profits over time often outweighs the appeal of a risky, high-return strategy that could potentially lead to substantial losses. So, while automation can be a powerful tool in your trading arsenal, it's also important to consider other strategies and factors. Always ensure you're managing your risk effectively and approaching trading with a realistic and informed perspective. ------------------------------------------------------------------------ Why Easy Trade Pro is Original? ---------------------------------------------------------------------------------- We developed Easy Trade Pro as a unique and comprehensive solution, and we decided to protect our code to preserve its originality. We invested significant time and effort into making it a realistic trading strategy simulator. The standout features that set Easy Trade Pro apart include: ☀ Versatile Stop Loss Mechanisms: Stop loss execution can be complex and often requires careful coding to work as intended. In most freely available open-source codes, stop losses are implemented using the Average True Range (ATR). ATR can be beneficial but has limitations: ☁ Lagging Indicator - Like most technical indicators, the ATR is a lagging indicator. This means it is based on past data, and so it may not accurately reflect future market volatility. If market conditions change rapidly, the ATR may not adjust quickly enough, potentially leading to suboptimal stop loss levels. ☁ No Directional Information - The ATR measures volatility, but it does not provide any indication of the direction of the trend. Therefore, it should not be used as a standalone tool for making trading decisions, but should be used in conjunction with other technical analysis tools that can provide directional cues. ☁ Inefficiency in Trending Markets - In strongly trending markets, ATR-based stops can sometimes be too far from the current price level. This could lead to larger losses if the price moves against your trade before hitting the stop loss. On the flip side, in less volatile, sideways markets, an ATR-based stop might be set too close to the entry point, leading to premature stop outs. ☁ Overoptimization Risk - If you're backtesting a trading strategy, there's a risk of overoptimizing your stop loss settings by fine-tuning them to past data. The best ATR multiplier that worked in the past might not necessarily work in the future, leading to potential performance issues. ☀ We countered these by implementing four different types of 'protect the trade' mechanisms: ✔ Fixed Percentage Stop Loss ✔ Trailing Stop Loss ✔ Stop Loss Moved to Entry Upon Reaching Certain Gain ✔ Stop Loss Moved to Entry Upon Reaching First Take Profit Order ("Custom Order"). ☀ Dual Exit Strategy: We incorporated two distinct methods of exiting a trade. The first uses our custom signals, while the second triggers exit at a certain percentage of gain. ☀ Multiple Take Profit Orders: You have the flexibility to establish up to four different sell orders. This feature enables you to fractionate your exit strategy according to your needs. You can choose to trigger these fractions based on our custom signals or determine your own exit points by setting targeted gains at a fixed percentage. ☀ Confirmation Candle System: This feature enhances trade precision by requiring confirmation candles after a buy or sell signal. This confirmation, dependent on the next candle's closing price, helps reduce false signals and improves entry and exit points. While our confirmation system is applicable to all custom buy signals, it's solely dedicated for the bearish reversal when it comes to sell signals. ☀ Universal Compatibility: Easy Trade Pro's Strategy Tester works perfectly with any asset class. The code can handle different contract types, including the SPX contracts and fractional assets like Bitcoin. It's optimized to ensure proper execution of trades without rounding issues. ☀ Bullish and Bearish Reversal candles: Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations. ☀ Non-Repainting Indicator: Our indicator signals are designed not to repaint. Once a signal appears, it stays fixed, offering a reliable tool for your trading decisions. ================================================== EXTENSIVE TECHNICAL DESCRIPTION ==================================================== Easy Trade Pro is versatile, allowing you to analyze market trends across any financial asset. With its rigorous testing, our tool can be used confidently on any timeframe, from 1D to 1min, whether you prefer longer-term or shorter-term trades. Although we recommend trading on timeframes between 1D and 1min, higher timeframes like 1W chart, can also provide broader insights. Our study combines a variety of popular technical indicators, such as RSI, Stochastic RSI, MACD, DMI, Bollinger Bands as well as relevant EMAs. On the volume side OBV and MFI. Using a data-driven approach, “Easy Trade Pro” analyzes historical market trends to identify optimal ways to combine these indicators with significant divergences between price and oscillators. On top of that the code considers relevant changes in market structure and liquidity grabs, to generate reliable and accurate signals for potential buy and sell opportunities. * ☎ --> Please not that MACD, BBs, and EMAs account for a minimal part of our script <--- ☎, If you're looking for a simpler tool, consider checking out our open-source indicator, 'RSI, SRSI, MACD, and DMI cross - Open source code'. You can find it here: With our customizable system, traders will be able to identify: 1) Three types of buy signals🐂,💰,💎 and sell signals 🐻,🔨,💀 2) Bullish and bearish reversal candles with support and resistance lines 3) Bull and bear momentum signals 4) A function that utilizes Color bars to identify the strength of the trend 5) Three customizable moving averages 6) Alerts direct to your email or phone 7) Advanced and customizable settings menu 8) Our software also includes a backtesting system that that allows users to test their trading strategies on historical data, to check how they would have performed in real-world market conditions. This can help refine a trading strategy and make more informed decisions. ------------------------------------------------------------------------------ 1) BUY AND SELL SIGNALS --------------------------------------------------------------------------------- Our buy and sell signals are generated using a custom combination of RSI, MFI, and Stochastic RSI levels, as well as relevant MACD and Stochastic RSI crosses. These indicators are carefully analyzed to identify potential trading opportunities and determine optimal entry and exit points for trades. RSI (Relative strength index) measures the strength of a security's price action, while the SRSI (Stochastic Relative Strength Index) is a momentum oscillator that measures the current price relative to its high and low range over a set period. The Money Flow Index (MFI) is another momentum indicator that uses both price and volume data to measure buying and selling pressure. MACD (Moving Average Convergence Divergence) is a popular technical indicator used in financial markets to analyze price trends and momentum. ▶ With our system, you'll be able to identify three different levels of buy signals: ◉ The first level of buy signal is represented by a 🐂 emoji and is a "Good Buy". This signal indicates a possible buying opportunity. It indicates that could be a good opportunity to enter in a long trade. It's important to note that, the "Good Buy" signal can sometimes be supplemented with a green "Bull" text and a flag plotshape positioned beneath the signal. In these scenarios, we categorize this as a "Good Buy Bull" signal. ◉ The second level of buy signal is represented by a 💰 emoji and is a "Great Buy". This signal indicates a stronger buying opportunity than the "Good Buy" signal. ◉ The third and strongest buy signal is represented by a 💎 emoji and is an "Incredible Buy". This signal indicates a stronger buying opportunity than the "Good Buy" and "Great Buy" signals ▶ With our system, you'll be able to identify three different levels of sell signals: ◉ On the sell side, the first level is represented by a 🐻 emoji and is a "Good Sell". This signal indicates a possible selling opportunity. It indicates that could be a good opportunity to exit a trade or open a short position. It's important to note that, the "Good Sell" signal can occasionally be accompanied by a red "Bear" text and a flag plotshape positioned beneath the signal. In such instances, we refer to this as a "Good Sell Bear" signal. ◉ The second sell signal is represented by a 🔨 emoji and is a "Great Sell". This signal indicates a stronger selling opportunity than the "Good Sell" signal. ◉ The third and strongest sell signal is represented by a 💀 emoji and is an "Incredible Sell". This signal indicates a stronger selling opportunity than the "Good Sell" and "Great Sell" signals. ------------------------------------------2) "BULLISH AND BEARISH REVERSAL CANDLES PLUS SUPPORT AND RESISTANCE LINES" ------------------------------------------------ Bullish and bearish reversal candles are specific candles that have more probability to reverse the trend. Our trading indicator is designed to identify bullish and bearish reversal candles. Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations. These candles are represented by blue and orange colors respectively by default. Additionally, the indicator also uses lines that are drawn at either the opening or closing of candles to help identify pivot points of support or resistance. These candles, lines color or shape are customizable in the settings menu. How can I benefit the most from bullish reversal candles? To make the most of bullish reversal candles, a powerful strategy is: E.g, 1D chart - Wait for the next 1 or 2 candles to close above the support line linked to the bullish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. A good tip is also to look for other signals (confluence), like a buy signal. Traders should decide based on their risk tolerance. Here below we can see an example of a bullish reversal candle in the BTC/USDT, 1D, chart. The system identify a bullish reversal candle (blue color), the next 2 candles are green and closed above the support blue line, in addition we have other bullish signals (confluence). How can I benefit the most from bullish reversal lines? Bullish reversal lines can help traders to identify key level of support and maintain control of their position until a clear break below occurs. In the example below we se how the price retrace to the support line: After touching the price bounce up. How can I benefit the most from bearish reversal candles? To make the most of bearish reversal candles, a powerful strategy is: E.g, 1D chart - Wait for the next 1 or 2 candles to close below the resistance line linked to the bearish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. Traders should decide based on their risk tolerance. Here below we can see an example of a bearish reversal candle in the ETH/USDT, 1D, chart. The system identify a bearish reversal candle (orange color), the next candle is red and closes below the resistance orange line. A good tip is also to look for other signals (confluence), like a sell signal. How can I benefit the most from bearish reversal lines? Bearish reversal lines can help traders to identify key level of resistance and maintain control of their position until a clear break above occurs. In the example below we se how the price bounce back to the resistance line and get rejected. ------------------------------------------------------------------------- 3) BULL AND BEAR MOMENTUM SIGNALS ----------------------------------------------------------------------- We analyzed factors such as buy or sell signals, long or short confirmation signals, DMI crossup or crossdown and breaks of market structure (BOS) or change of character (CHoCh) to determine the strength and direction of the trend. These study give us bull trend or bear trend signals that can help traders identify potential trading opportunities and make informed decisions. These conditions are represented by a green word "BULL" and a flag shape below (bull momentum) and by a red word "BEAR" and a flag shape above (bear momentum) respectively by default. These plots shapes are customizable in the settings menu. How can I benefit the most from bull momentum signals? To make the most of bull momentum signals, a powerful strategy is: E.g, 1D chart - Look for confluence. If bull signal comes with a "Good Buy 🐂" in the same candle the signal is more strong. Another good combo is to look for a bullish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision. In the picture below we can see an example of a bull momentum signal in the US500, 1D, chart. How can I benefit the most from bear momentum signals? To make the most of bear momentum signals, a powerful strategy is: E.g, 1D chart - Look for confluence. If bear signal comes with a "Good Sell 🐻" in the same candle the signal is more strong. Another good combo is to look for a bearish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision. In the picture below we can see an example of a bear momentum signal in combo with a sell signal, NETFLIX, 1D, chart. -------------------------------------------------------------- 4) "COLOR BARS THAT INDICATE THE STRENGTH OF THE TREND ----------------------------------------------------- This code is responsible for changing the color of the bars on a chart based on certain conditions. The gradient colors are defined for green and red, and the algorithm checks if the current bar is within a certain range of either a bearish reversal or bullish reversal candle and whether the price is above or below certain exponential moving averages or if important break of market structure occurs. Ultimately, this feature helps traders visually identify potential trends and market shifts and avoid getting distracted by price fluctuations. Please note that every gradient of color can be customize by the user. We set 3 different bullish colors and 3 different bearish colors. Below the picture of the settings menu related to the bar color. ----------------------------------------------------------------------5)THREE CUSTOMIZABLE MOVING AVERAGES ---------------------------------------------------------------------- You can choose up to three moving averages, any length and any type like SMA, EMA, WMA, HMA, RMA, SWMA and VWMA. Furthermore, you have the freedom to adjust the color and width of the lines to your preference. Below the picture of the settings menu related to the moving averages. ----------------------------------------------------------------------6) ALERTS DIRECT TO YOUR EMAIL OR PHONE -------------------------------------------------------------------- Our alert feature sends real-time notifications directly to your email or phone when a signal is generated, allowing you to take immediate action and stay ahead of the market. With our system, you first establish your own rules for trading in the strategy tester - this includes your criteria for entering and exiting trades. Once you've defined these conditions, our system will start sending you alerts. These alerts will be triggered whenever your specified conditions are met. So, if the market matches your 'enter trade' conditions, you'll receive an alert prompting. Similarly, when your 'exit trade' conditions are met, you'll receive another alert. Remember, these alerts are purely based on the conditions you set. Once the condition is met, you will receive alerts directly to your email or phone when enter and exit a trade based on your custom conditions. To make sure you receive these notifications click on notifications tab. ---------------------------------------------------------------7) ADVANCED AND CUSTOMIZABLE SETTINGS MENU---------------------------------------------------------------------- We designed Easy Trade indicators with traders in mind, so it's user-friendly, easy to navigate and users can customize inputs, style, and colors of every feature in the indicator's settings menu. -----------------------------------------------------------------------8) EASY TRADE PRO - BACKTESTING SYSTEM---------------------------------------------------------------------- Easy Trade Pro features a highly effective and realistic backtesting system, designed to mirror as closely as possible the real-world scenarios of entering and exiting trades. Step 1: Open the settings menu of the Indicator. Once opened the settings menu click on properties. Decide on the capital you wish to invest. Choose whether to use contracts or USD and determine the size of your orders. For the sake of realism, we recommend not exceeding 25% of your capital per order. However, if you decide to utilize your entire capital, make sure to adjust your stop loss accordingly. For instance, if you have a capital of 10K and use 10K with a stop loss at 2%, your potential loss would be $200. Conversely, if you use only 2K of your 10K capital with a stop loss at 10%, you would still lose the same 2% of your capital. To make your simulation even more authentic, consider incorporating broker fees or commissions into your calculations. For example, spot market fees are typically around 0.10%. If you're backtesting markets with low liquidity, consider factoring in slippage as well. Step 2: Navigate to the 'Inputs' section and scroll down until you come across 'Backtesting System - Strategy Test'. Once you locate this, click on the box and activate the 'USE STRATEGY SYSTEM' option by checking the tick box. Also You will then need to set a 'Start Date' and 'End Date', establishing a specific time period during which you wish to test your strategy. Otherwise you can consider to use the deep backtesting feature. Step 3: It's now time to establish the conditions for entering a trade. You can choose from five different types of custom buy signals: Good Buy, Good Buy Bull, Great Buy, Incredible Buy, and Bullish Reversal. Note that 'Great Buy' and 'Incredible Buy' are rare signals, so we advise against using them frequently in mechanical strategy tests; instead, consider them more for manual live tests. For more consistent results, we recommend using the other buy signals. After determining your preferred buy signal, you can choose how many confirmation candles you wish to wait for before entering a trade. A 'confirmation' means that if the next candle closes above the opening or closing price of the chosen buy signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (close > open) or red. You can set the number of confirmation candles in different time frames: below 2h, between 2h and 10h, and above 10h. Step 4: It's now time to safeguard your trade by managing risk. You can choose to implement a stop loss, expressed in percentage terms, or opt for a trailing stop. A trailing stop is a type of stop loss order that moves with the market price. It is designed to protect gains by enabling a trade to remain open and continue to profit as long as the market price is moving in a favorable direction. However, the trade closes if the market price changes direction by a specified amount (the 'trailing stop distance'). Additionally, you can minimize losses and move the stop loss to your entry point once the price reaches a certain percentage of profit. This strategy can help secure potential gains while limiting the potential for losses. Step 5: Now it's time to set the conditions for exiting the trade. You have the option to divide your exit into a maximum of four parts, with each part representing 25% of the position size. For each take profit point, you can choose from three different custom sell signals: Good Sell, Good Sell Bear, and Bearish Reversal. Similarly, the concept of confirmation candles also applies here, but in this case, the candles are not closing above. A 'confirmation' for a sell signal means that if the next candle closes below the opening or closing price of the selected sell signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (open > close) or red (close < open). So, when you're looking to sell, a confirmation would occur if the next candlestick's closing price is lower than the opening or closing price of the candlestick that triggered the sell signal. This indicates a potential bearish trend, providing the confirmation to execute the sell order. Additionally, we've introduced a feature that allows you to move your stop loss to the entry point whenever the first take profit (1TP) is reached, which equates to hitting one custom sell signal. Step 6: We've also designed an alternative method for taking profits. With this approach, you can choose to exit your position once a fixed percentage gain from the entry point is reached. For instance, you might decide to exit when a 10% profit is achieved. Similarly to the previous method, this approach allows you to choose up to four exit points and determine the proportion of your position you want to close at each stage. Conclusion: Easy Trade Pro provides users with various options for entering and exiting trades. To effectively utilize the indicator, we strongly recommend conducting thorough backtesting and considering the results across your preferred trading pairs. It is advisable to analyze a substantial number of trades, ideally exceeding 100 trades, to obtain reliable insights into the indicator's performance. This approach will help you gain a better understanding of how Easy Trade Pro aligns with your trading strategy and objectives. ❗Keep attention❗ It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions. It is also important to be aware of the limitations of simulated performance results. Hypothetical or simulated results do not represent actual trading, and since trades have not been executed, results may be over- or under-compensated for market factors such as lack of liquidity. Simulated trading programs are also designed with the benefit of hindsight, and no representation is being made that any account will achieve profits or losses similar to those shown. Therefore, our indicators are for informative purposes only and not intended to be used as financial advice. We encourage traders to use our indicators as part of a well-rounded trading strategy and to always be aware of the risks involved in trading. Remember that past performance is not indicative of future results and always trade responsibly.
Strategi Pine Script®
oleh Trading_Paradise
6
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits. Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend. The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines. Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits. Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels. The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading. Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now! General Comments This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts. Detailed Description The “Flash” script considers the following indicators for the generation of trading signals: 1. Momentum-RSI 2. ‘Super-Trend’-Analysis 3. EMA-Strategy 1. Momentum-RSI • This indicator signals the strength of the underlying upward- or downward-trend. • The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend. • The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals). • This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend. Graph 1 shows this concept: • The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods. Example (graph 2): 2. Super-Trend Analysis • The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively). • If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered. • The vice-versa approach can be considered for short entries. Graph 3 explains this concept: 3. Exponential Moving Average / EMA-Strategy The functionality of this EMA-element of the strategy has been programmed as follows: • The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals. • Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line. • Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line. An example is shown in graph 4 below: We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement. 4. Bringing it all together This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy. The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met: 1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5): 2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively. 3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively. The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success. Example for Long-Entry (graph 6): When these conditions are met, our Long position is opened. Example for Short-Entry (graph 7): Trade Management Options (graph 8) Option 1 In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters. The following settings of the supertrend-indicator can be changed and optimized (graph 9): The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment. Option 2 (graph 10): Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart. Settings options (graph 11): The following settings can be changed for the three elements of this strategy: 1. (Length Mom-Rsi): Length of our Mom-RSI indicator. 2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals. 3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend 4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind 5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind 6. The backtesting period can be adjusted: Start and End time of BackTest 7. Dollar cost per position: this is relevant for 100% fully automated trading. 8. Trade direction can be adjusted: LONG, SHORT or BOTH 9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 ) Display options on the charts graph 12): 1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts. 2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend. Other comments • 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.
Strategi Pine Script®
oleh JS_TechTrading
4
Pro Divergence [regular + hidden] by TradingClue█ Pro Divergence is my new divergence-based toolkit that will help you to spot lucrative opportunities in all kinds of markets. I've developed toolkits and strategies that use divergences for many years, e.g. AutoDivergence and CCIDivergence . Pro Divergence is my latest development and benefits from those yearlong experiences. The main algorithm to detect divergences has changed from using linear regressions and moving averages to algorithmic trendline detection like I've been using in TD Lines . This new approach supports the detection of regular divergences but also hidden divergences can be identified. Before going more into the details of the mechanics of Pro Divergence, let's recap, what divergences are all about when it comes to trading. █ Regular Divergence The basic idea is pretty simple: If price goes in the opposite direction than some other technical indicator - in most cases an oscillator - we speak of a divergence. A regular divergence might be a signal for a trend reversal. That's it. For example, if the price is currently rising, while at the same time Momentum is falling - it might be time for a reversal and the price of an asset is about to fall soon. If there are additional indications to confirm the signal, e.g. if RSI is in the overbought area, it might be a good idea to go short on that specific asset. Regular bullish divergences are indicated when price is forming lower lows while an oscillator shows higher lows. Regular bearish divergences are indicated when price is forming higher highs while an oscillator shows lower highs. █ Hidden Divergence While regular divergences indicate trend reversals, hidden divergences indicate a trend continuation. When the price is making higher lows and the oscillator is showing lower lows, we speak of a bullish hidden divergence. When the price is making lower highs and the oscillator shows higher highs, it's a bearish hidden divergence. These rules for identifying divergences are pretty simple and straightforward. And they are also confusing at times. But that's what Pro Divergence is helping you with: trade based on customizable signals to identify all kinds of divergences. You could either use the strategy settings of the toolkit to optimize the properties to show winning backtesting results. Or you use the signals as an extra confirmation to some other kind of signal/ strategy you are working with. █ Summary of all current features • Oscillator: choose between CCI, Momentum, MACD, or RSI. All oscillators-settings are customizable. • RSI-filter: in some cases, the quality of the signals can be improved by an RSI filter, e.g. a bullish signal would only be valid if RSI is in the oversold area. Set the RSI period and the oversold/ overbought levels to your preferred values. • You can display all divergences on the chart to get an idea of the current price action. Or you can pick any combination of signals you would like to include in a backtest. Possible signals are: regular bullish divergence, regular bearish divergence, hidden bullish divergence, hidden bearish divergence • Exits: there are many ways to get exit signals - combinations of the below options are possible:    • fixed profit targets/ stop losses based on ticks    • Exit when momentum reverses    • Exit when price touches the opposite Bollinger Band (e.g. a long position will be closed when price touches the upper Bollinger Band). The settings for the Bollinger Bands are customizable. • Entry: you can choose only to enter a trade if momentum is going in the same direction as the direction of your trade (e.g. only go long if momentum is rising) • time and date filer    • Do a backtest only in a given time range (maybe you're not interested in the whole range of historical data when trading in a higher timeframe. Or you would like to do some kind of walk forward analysis)    • Only trade during special times of a day, e.g. only trade during the first hours of a trading session Since this strategy is making heavy use of math and technical indicators, it is not tied to a certain asset class or timeframe. It was tested successfully on a large number of financial instruments like stocks, crypto, forex, and others.
Strategi Pine Script®
oleh TradingClue
NRTH_ Smart SignalsA Custom Unique indicator by NRTH_ Comes included with the Premium Package. NRTH_ Smart Signals is made up of over 5+ indicators and custom calculation methods. Get access to a full set of trading tools & relevant data all within one indicator to give you the levels of confluence you need. Smart Signals works in any market & allows users to: Detect the direction of trends in the price using two different algorithms designed for both trend following and contrarian traders. Get automatic pivot point levels in real-time. Filter out noise with the MA Trend Filter Built-In Alerts Visual Risk Management Customizable Entry Rules 2 Calculation Methods Get Confirmation Use our MA Trend filter to detect the direction of trends for any asset & on any timeframe allowing traders to increase their confidence in positions and follow trends. The larger the cloud, the larger the trend. Choose between the two calculation methods: Leading More sensitive Designed to predict moves based on market data Lagging Less sensitive Waits for confirmation signals Both calculation methods have the possibility to adjust the sensitivity of these signals to market price variations, as well as the option to make them less sensitive to ranging markets so that you can trade only the variations you want. The algo uses both momentum and trend calculation to find an entry, highly recommended use with the built-in MA Filter for best results. Trade 24/7 without pressing a button Smart Signals has integrated alerts which give you the ability to automate your signals with 3rd party applications. Simply adjust the sensitivities for your market and trade on autopilot. You can also use Heikin Ashi Charts with the algo IF you only place limit orders on the exact price line that the trade outputs to ensure accurate real-time results (Heikin Ashi trading is NOT recommended for automated trading, manual limit orders must be placed in order to match real-time results with backtested data) Backtesting Results Info Period 7/7/2021-15/11/2021 Entry value at $1000 with 10x leverage Binance standard taker fee rate (0.04%) ATR Exits : 1:2 RR ------------------------------------------- Disclaimer Copyright NRTH_ Indicators 2021. ​‍NRTH_ and all affiliated parties are not registered as financial advisors. The products & services NRTH_ offers are for educational purposes only and should not be construed as financial advice. You must be aware of the risks and be willing to bear any level of risk to invest in financial markets. Past performance is not necessarily indicative of future results. NRTH_ and all individuals associated assume no responsibility for your trading results or investments. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. Instagram
Strategi Pine Script®
oleh NRTH_Indicators
1
Smart Entry BETAA Custom Unique indicator by NRTH_ Comes included with the Premium Package. Indicator features Built-In Alerts Visual Risk Management Customizable Entry Rules Usage Tips Smart Entry is currently a BETA algo. we are still in the process of tweaking and programming it only give entry signals when they are confirmed, and work of very strict parameters to allow for trading all the way down to the 5m timeframe. It is currently at a stage where it can produce profitable trades or even just act as a confirmation signal in use with another strategy, but this project will be ongoing until we can obtain high profitability levels on very low timeframes. The algo uses both momentum and trend calculation to find an entry, highly recommended use with the built-in MA Filter for best results. Works for all markets with the ability to customize to your liking. Backtesting Results Info Period 1/1/2021-1/10/2021 Entry value at $1000 with 10x leverage Binance standard taker fee rate (0.04%) ATR Exits : 1:2.9 RR ------------------------------------------- Disclaimer Copyright NRTH_ Indicators 2021. ​‍NRTH_ and all affiliated parties are not registered as financial advisors. The products & services NRTH_ offers are for educational purposes only and should not be construed as financial advice. You must be aware of the risks and be willing to bear any level of risk to invest in financial markets. Past performance is not necessarily indicative of future results. NRTH_ and all individuals associated assume no responsibility for your trading results or investments. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Strategi Pine Script®
oleh NRTH_Indicators
2
VWMA with kNN Machine Learning: MFI/ADXThis is an experimental strategy that uses a Volume-weighted MA (VWMA) crossing together with Machine Learning kNN filter that uses ADX and MFI to predict, whether the signal is useful. k-nearest neighbours (kNN) is one of the simplest Machine Learning classification algorithms: it puts input parameters in a multidimensional space, and then when a new set of parameters are given, it makes a prediction based on plurality vote of its k neighbours. Money Flow Index (MFI) is an oscillator similar to RSI, but with volume taken into account. Average Directional Index (ADX) is an indicator of trend strength. By putting them together on two-dimensional space and checking, whether nearby values have indicated a strong uptrend or downtrend, we hope to filter out bad signals from the MA crossing strategy. This is an experiment, so any feedback would be appreciated. It was tested on BTC/USDT pair on 5 minute timeframe. I am planning to expand this strategy in the future to include more moving averages and filters.
Strategi Pine Script®
oleh lastguru
9
BuyTheDipWell, I often had arguments in online forum with a guy who claimed to time the market perfectly without any technical analysis or prior experience. He often claimed that technical analysis does not work and it only works when you trade on other's emotions. He also argued that algorithmic trading isn't profitable - if so, everyone would do that. Hence, I thought I will convert his idea to algorithm. In his own words, the strategy is as below: Chose an instrument which is in full uptrend. Wait for the panic sell and buy the dip Once market recovers back exit immediately It seems to do just fine with indexes. But, not so good when it comes to stocks.
Strategi Pine Script®
oleh Trendoscope
11
Jarvis for EURUSD by Goldman ArmiThis strategy is called JARVIS after the famous AI from the MARVEL movie Iron Man. It is an improvement of the Copernicus Strategy to get better results. More exactly I was aiming to obtain over 50% of the number of trades profitable, for every pair provided (see the title). The strategy tester does not include leverage trading, please keep that in mind and feel free to change the parameters of the volume for the position in the strategy settings to see the closer to reality results. The setup for this strategy is more complicated because it includes 3 averages, all of them calculated with prices obtain by various formulas for each one of them and I call this: Sophisticated Moving Average (Copyright). Each of the 3 averages are applied to different timeframes and have different values. All of these parameters are configured separately for every trading pair and this is why I am publishing them separately. There are not a lot of trades in this strategy, the average is around 3/month for EURUSD and the result you see in this strategy is from January 2020 to this date of publishing. You can use the Tradingview alert services to configure this to execute (webhook) on your exchange/broker, because strategies have now the possibility to send alerts. For other questions please send me a message.
Strategi Pine Script®
oleh armigoldman
Jarvis for ETHUSD by Goldman ArmiThis strategy is called JARVIS after the famous AI from the MARVEL movie Iron Man. It is an improvement of the Copernicus Strategy to get better results. More exactly I was aiming to obtain over 50% of the number of trades profitable, for every pair provided (see the title). The strategy tester does not include leverage trading, please keep that in mind and feel free to change the parameters of the volume for the position in the strategy settings to see the closer to reality results. The setup for this strategy is more complicated because it includes 3 averages, all of them calculated with prices obtain by various formulas for each one of them and I call this: Sophisticated Moving Average (Copyright). Each of the 3 averages are applied to different timeframes and have different values. All of these parameters are configured separately for every trading pair and this is why I am publishing them separately. There are not a lot of trades in this strategy, the average is around 1/month. You can use the Tradingview alert services to configure this to execute (webhook) on your exchange/broker, because strategies have now the possibility to send alerts. For other questions please send me a message.
Strategi Pine Script®
oleh armigoldman
Jarvis for BTCUSD by Armi GoldmanThis strategy is called JARVIS after the famous AI from the MARVEL movie Iron Man. It is an improvement of the Copernicus Strategy to get better results. More exactly I was aiming to obtain over 50% of the number of trades profitable, for every pair provided (see the title). The strategy tester does not include leverage trading, please keep that in mind and feel free to change the parameters of the volume for the position in the strategy settings to see the closer to reality results. The setup for this strategy is more complicated because it includes 3 averages, all of them calculated with prices obtain by various formulas for each one of them and I call this: Sophisticated Moving Average (Copyright). Each of the 3 averages are applied to different timeframes and have different values. All of these parameters are configured separately for every trading pair and this is why I am publishing them separately. There are not a lot of trades in this strategy, the average is around 1/month. You can use the Tradingview alert services to configure this to execute (webhook) on your exchange/broker, because strategies have now the possibility to send alerts. For other questions please send me a message.
Strategi Pine Script®
oleh armigoldman
Hull Strategy [Bitduke]Description The Hull Moving Average (HMA) was developed by Alan Hull for the purpose of reducing lag, increasing responsiveness while at the same time eliminating noise. Its calculation is elaborate and makes use of the Weighted Moving Average (WMA). It uses two lagged hull moving averages at the intersection of which a change in trend is determined. Risk Management Risk is managed by limiting the loss per trade (in%) using stop loss variable. Improvements Can be improved by experiments with stop loss and take profit. Backtesting Bitmex XBTUSD Timeframe 3H Stop 2%, take profit : n/a 193.5% profit 22.42% drawdown FTX BTC-PERP Timeframe 3H Stop 2%, take profit : n/a 187.5% profit 14.79% (!) drawdown FTX SHIT-PERP Timeframe 3H Stop 2%, take profit : n/a 112.5% profit 13.79% (!) drawdown
Strategi Pine Script®
oleh Bitduke
1
BitMEX pump catcher - MACDThis is a modified version of the BitMEX pump catcher by Jomy . I have tweaked the algorithm to use the difference in MACD to get the correct direction of entries rather than using direction of candles which are not always indicative of trend direction. These changes increase net profit, profitable trades, while reducing drawdown. Below is a copy and paste of Jomy's explanation of the algorithm. What is going on here? This strategy is pretty simple. We start by measuring a very long chunk of volume history on BitMEX:XBTUSD 1 hour chart to find out if the current volume is high or low. At 1.0 the indicator is showing we are at 100% of normal historical volume . The blue line is a measure of recent volume! This indicator gets interested when the volume drops below 90% of the regular volume (0.9), and then comes back up over 90%. There's usually a pump of increased price activity during this time. When the 0.9 line is crossed by the blue line, the indicator surveys the last 2 bars of price action to figure out which way we're going, long or short. Green is long. Red is short. To exit the trade we use a 7 period fast ema of the volume crossing under an 11 ema slower period which shows declining interest in the market signifying an end to the pump or dump. The profit factor is quite high with 5x leverage, but historically we see 50% drawdown -- very risky. 1x leverage looks nice and tight with very low drawdown. Play with the inputs to see what matches your own risk profile. I would not recommend taking this into much lower timeframes as trading fees are not included in the profit calculations. Please don't get burned trading on stupid high leverage. This indicator is probably not going to work well on alts, as Bitcoin FOMO build up and behavior is different. This whole indicator is tuned to Bitcoin , and attempts to trade only the meatiest part of the market moves. Jomy should get full credit to this indicator
Strategi Pine Script®
oleh ahancock
27
Full Range Trading Strategy with DCA - Crypto, Forex, Stocks Introduction This is a Pine 4 range trading strategy. It has a twin study with several alerts. The design intent is to produce a commercial grade signal generator that can be adapted to any symbol and interval. Ideally, the script is reliable enough to be the basis of an automated trading system web-hooked to a server with API access to crypto, forex and stock brokerages. The strategy can be run in three different modes: long, short and bidirectional. As a range trading strategy, the behavior of the 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. 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. When trading in “Ping Pong” mode long and short positions are intermingled continuously as long as there exists a detectable vertex. Unfortunately, this can work against your backtest profitability on long duration trends where prices continue in a single direction without pullback. I have designed various features in the script to compensate for this event. A well configured script should perform in a range bound market and minimize losses in a trend. I also have a trend following version of this script for those not interested in trading the range. Please be aware these are two types of traders. You should know who you are. This script employs a DCA feature which enables users to experiment with loss recovery techniques. This is an 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 TV properties tab. The inputs for this feature include a limiter to prevent your account from depleting capital during runaway markets. This implementation of DCA does not use pyramid levels. Only the order size on subsequent new trades are affected. Pyramids on the other hand increase the size of open positions. If you are interested in seeing pyramids in action please see the trend version of this script which features both DCA and pyramids. While DCA is a popular feature in crypto trading, it can make you a “bag” holder if your not careful. In other markets, especially margin trading, you’ll need a well funded account and much trading experience to manage this feature safely. Consecutive loss limit can be set to report a breach of the threshold value. Every stop hit beyond this limit will be reported on a version 4 label above the bar where the stop is hit. Use the location of the labels along with the summary report tally to improve the adaptability of system. Don’t simply fit the chart. A good trading system should adapt to ever changing market conditions. On the study version the consecutive loss limit can be used to halt live trading on the broker side (managed manually). Design This script uses twelve indicators on a single time frame. The original trading algorithms are a port from a much larger program on another 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 form the basis of the entry and exit points. The vertices are calculated using one of five featured indicators. Each indicator is actually a composite of calculations which produce a distinct mean. This mathematical distinction enables the script to be useful on various instruments which belong to entirely different markets. In other words, at least one of these indicators should be able generate pivots on an arbitrarily selected instrument. Try each one to find the best fit. The entire script is around 1800 lines of Pine code which is the maximum incidental size given the TradingView limits: local scopes, run-time duration and compile time. I’ve been working on this script for nearly two years and have tested it on various instruments stocks, forex and crypto. It performs well on higher liquidity markets that have at least a year of historical data. Although the script can be implemented on any interval, it has been optimized for small time frames down to 5 minutes. The 10 minute BTC/USD produces around 500 trades in 2 ½ months. The 1 hour BTC/USD produces around 1300 trades in 1 ½ years. Originally, this script contained both range trading and trend following logic but had to be broken into separate scripts due to the aforementioned limitations. Inputs to the script use cone centric measurements in effort to avoid exposing adjustments to the various internal indicators. The goal was to keep the inputs relevant to the actual trade entry and exit locations as opposed to a series of MA input values and the like. As a result the strategy exposes over 50 inputs grouped into long or short sections. Inputs are available for the usual minimum profit and stop-loss as well as safeguards, trade frequency, DCA, modes, presets, reports and lots of calibrations. The inputs are numerous, I’m aware. Unfortunately, at this time, TradingView does not offer any other method to get data in the script. The usual initialization files such as cnf, cfg, ini, json and xml files are currently unsupported. Example configurations for various instruments along with a detailed PDF user manual is available. Indicator Repainting And Anomalies Indicator repainting is an industry wide problem which mainly occurs when you mix backtest data with real-time data. It doesn't matter which platform you use some form of this condition will manifest itself on your chart over time. The critical aspect being whether live trades on your broker’s account continue to match your TradingView study. Tackling this repainting issue has been a major project goal of this script. Based on my experience with Pine, most of the problems stem from TradingView’s implementation of multiple interval access. Whereas most platform provide a separate bar series for each interval requested, the Pine language interleaves higher time frames with the primary chart interval. The problem is exacerbated by allowing a look-ahead parameter to the Security function. The goal of my repaint prevention is simply to ensure that my signal trading bias remains consistent between the strategy, study and broker. That being said this is what I’ve done address this issue in this script: 1. This script uses only 1 time frame. The chart interval. 2. Every entry and exit condition is evaluated on closed bars only. 3. No security functions are called to avoid a look-ahead possibility. 4. Every contributing factor specified in the TradingView wiki regarding this issue has been addressed. 5. I’ve run a 10 minute chart live for a week and compared it to the same chart periodically reloaded. The two charts were highly correlated with no instances of completely opposite real-time signals. The study does indeed bring up the TV warning dialog. The only reason for this is because the script uses an EMA indicator which according to TradingView is due to “peculiarities of the algorithm”. One issue that comes up when comparing the strategy with the study is that the strategy trades show on the chart one bar later than the study. This problem is due to the fact that “strategy.entry()” and “strategy_exit()” do not execute on the same bar called. The study, on the other hand, has no such limitation since there are no position routines. Please be aware that the data source matters. Cryptocurrency has no central tick repository so each exchange supplies TradingView its feed. Even though it is the same symbol the quality of the data and subsequently the bars that are supplied to the chart varies with the exchange. This script will absolutely produce different results on different data feeds of the same symbol. Be sure to backtest this script on the same data you intend to receive alerts for. Any example settings I share with you will always have the exchange name used to generate the test results. Usage 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 configs that I use for my own trading that I can share with you along with a PDF which describes each input in detail. To get hands on experience in setting up your own symbol from scratch please follow the steps below. The input dialog box contains over 50 inputs separated into five sections. Each section is identified as such with a makeshift separator input. There are three main areas that must to be configured: long side, short side and settings that apply to both. The rest of the inputs apply to DCA, reporting and calibrations. The following steps address these three main areas only. You will need to get your backtest in the black before moving on to the more advanced features. 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 3. 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 3 and enable “Apply Red Base To Base Margin”. Step 10. Go to Section 4 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. Return to Section 3 and 4 and turn off “Base To Base Margin” which was enabled in steps 9 and 10. Step 13. Turn off Show Markers in Section 2. Step 14. 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. This is a fixed value minimum profit and stop loss. Also 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. On the study version, the stop is executed at the close of the bar. Step 15. 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 16. Take a look at the chart. Trades should be showing along the markers plotted earlier. Step 17. 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 18. Step 18. Improve the backtest profitability by adjusting the “Long Entry Net Change” and “Long Entry ROC” in Section 3. Step 19. Improve the backtest profitability by adjusting the “Short Entry Net Change” and “Short Entry ROC” in Section 4. Step 20. Improve the backtest profitability by adjusting the “Sparse Long Delta” in Section 3. Step 21. Improve the backtest profitability by adjusting the “Chase Long Delta” in Section 3. Step 22. Improve the backtest profitability by adjusting the “Long Adherence Delta” in Section 3. This field requires the “Adhere to Rising Trend” checkbox to be enabled. Step 23. Try each checkbox in Section 3 and see if it improves the backtest profitability. The “Caution Lackluster Longs” checkbox only works when “Long Caution Mode” is enabled. Step 24. Improve the backtest profitability by adjusting the “Sparse Short Delta” in Section 4. Step 25. Improve the backtest profitability by adjusting the “Chase Short Delta” in Section 4. Step 26. Improve the backtest profitability by adjusting the “Short Adherence Delta” in Section 4. This field requires the “Adhere to Falling Trend” checkbox to be enabled. Step 27. Try each checkbox in Section 4 and see if it improves the backtest profitability. The “Caution Lackluster Shorts” checkbox only works when “Short Caution Mode” is enabled. Step 28. Enable the reporting conditions in Section 5. Look for long runs of consecutive losses or high debt sequences. These are indications that your trading system cannot withstand sudden changes in market sentiment. Step 29. 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 Macro indicator captures the tallest peaks and valleys. Step 30. Apply the backtest settings to the study version and perform forward testing. This script is open for beta testing. After successful beta test it will become a commercial application available by subscription only. I’ve invested quite a lot of time and effort into making this the best possible signal generator for all of the instruments I intend to trade. I certainly welcome any suggestions for improvements. Thank you all in advance.
Strategi Pine Script®
oleh tradingtudi
8
Scrybblez Strategy## Scrybblez Strategy ## How does this strategy work? This strategy works particularly well with Bitcoin and can be applied to volatile coins with big swings, but properly configured it will perform decently coins with smaller movements. Request access for a trial here or by twitter to @scrybblez It comes preconfigured with settings for 202 minutes, and already takes into account that each transaction will have a commission of 0.075% (Binance and Bitmex both have this comission at the moment) and assumes you'll be starting with a capital of 100,000 and put 100% of this capital into each trade. This works for Bitcoin but fails for some coins when there's not enough liquidity, to have the strategy work with smaller coins change your capital down from 100,000 to 1 or 5 (this will basically be telling Tradingview that you have 1-5 BTCs to trade and not 100,000 BTC). What timeframes does it work on? The strategy is particularly setup to work on 202 minutes but will perform well in 1h-6h timeframes. To use it in different timeframes to its optimum output mainly focus on increasing/decreasing accordingly the following values: - Bull/Bear EMA Range - Upper StopLoss band - Lower StopLoss band Noise filters play a smaller (but important) role on avoiding too many false entries. - Bull noise filter - Bear noise filter What are all these options I see ? 0.Shorting Toggle this option on/off depending on if you are in a platform that allows you to short (Bitmex, Bitfinex,...) or a platform that does not allow you to do so (Binance, KuCoin,...). 1. Time function This strategy comes equipped with a time function that allows you to backtest from any given date to any given date. Properties: - From Year - From Month - From Day - To Year - To Month - To Day 2. Noise Filtering/Smoothing To avoid too many false entries the strategy filters noise with several algorithms, you can enable/ disable this Noise filter by turning it on/off with "Use Smoothing" and can configure it's noise cleaning properties with other properties. You can, if you wish, colour your background to easily identify what's the current trend we're on (bear in mind that the indicator does not necessarily exit on Bull/Bear trends if it detects them as temporary or weak ones). Properties: - Use Smoothing - Bull noise filter - Bear noise filter - Color Bull/Bear Runs 3. StopLoss Bands Initially both bands were being used to terminate entries if crossed, but right now they work in conjunction with other internal calculations to determine if we should enter a trade and in minor degree to exit. With the latest changes included in the algorithm, we do not use SL bands to IMMEDIATELY exit positions, but the option is there. Poperties: - Upper SL Band - Lower SL Band - Use SL Bands to Open Positions. - Use SL Bands to Close Positions. 4.Ichimoku By turning this on, you'll plot Ichimoku with Bitcoin settings, you can change it to its original settings by clicking the next option. Can you give me examples on how well it performs? Following this strategy from the 1st of January of 2017 until today 7th of September of 2018 would've netted you (comission already substracted) 49286% returns. Following this strategy from the 1st of September of 2017 until today 7th of September of 2018 would've netted you (comission already substracted) 3941% returns. Following this strategy from the 1st of January of 2018 until today 7th of September of 2018would've netted you (comission already substracted) 583.96% returns. Give time to the strategy
Strategi Pine Script®
oleh Scrybblez
33
[Autoview][BackTest] Blank R0.13BThis is a fork of JustUncleL's Dual MA Ribbons R0.13 It is now a blank template for making new strategies / alerts for autoview The changes are as follows: Removed actual algo Establish functions for long Signal, long Close Signal and short Signal, short Close Signal to minimize the places code must be edited to update / replace algos Make allow Long and allow short and invert trade directions independent options Added support for alternate candle types Added autoset backtest period feature, and optional coloring Moved strategy calls in to functions so they can all be commented out or activated / disabled in a single block at the top of the script
Strategi Pine Script®
oleh yatrader2
1
📊 Multi-Timeframe High/Low Strategy Pro v40.0📊 Multi-Timeframe High/Low Strategy Pro v40.0 (Mustang Algo) 🎯 OVERVIEW Advanced trading strategy that identifies and trades breakouts of key support and resistance levels across multiple timeframes. Features intelligent pyramiding, ATR-based risk management, and comprehensive backtesting capabilities. Now upgraded to Pine Script v6 for enhanced performance and compatibility. ✨ KEY FEATURES 📈 Multi-Timeframe Levels: - Yesterday's High/Low - Today's High/Low (intraday) - Last Week's High/Low - Last Month's High/Low - Last Year's High/Low 🔥 Advanced Position Management: - Pyramiding up to 100 simultaneous positions - Configurable equity allocation per trade (0.1% - 100%) - Daily trade limiter to control overtrading - Smart position sizing with percentage-based allocation 🎯 Flexible Entry Signals: - 10 Long entry options (breakouts above key levels) - 10 Short entry options (breakdowns below key levels) - Mix and match any combination of signals - Real-time alerts for all level breaks 🛡️ Risk Management: - ATR-based or Percentage-based Stop Loss - ATR-based or Percentage-based Take Profit - Time-based exits (exit after X bars) - Precise price-based exits using limit/stop orders - Entry price calculation for accurate TP/SL placement 📊 Visual Features: - Clean, modern design with color-coded levels - Customizable labels with emojis for easy identification - ATR bands and histogram visualization - Real-time position information panel - Adjustable line lookback period (10-500 bars) ⚙️ HOW TO USE 1️⃣ Enable Strategy: • Check "▶️ Enable Strategy" in Backtesting Settings • Optionally set date range filter for testing specific periods 2️⃣ Select Entry Signals: • Choose which level breaks trigger Long entries (⬆️) • Choose which level breaks trigger Short entries (⬇️) • Can combine multiple signals for complex strategies 3️⃣ Configure Exits: • Enable Take Profit and/or Stop Loss • Choose between Percentage or ATR-based calculations • Set percentage values (e.g., 10% TP, 5% SL) • Optionally enable time-based exit (bars) 4️⃣ Advanced Options: • Enable Pyramiding for multiple concurrent positions • Set max number of trades per day (1-1000) • Adjust position sizing per trade (0.1-100%) 📋 CONFIGURATION PARAMETERS Visual Settings: - Toggle individual levels on/off - Line lookback length (10-500 bars) - Label size (large/normal/small/tiny) - Label color customization - Label positioning offset (0-50) ATR Settings: - ATR Period (default: 14, range: 1-200) - ATR Multiplier (default: 2.0, range: 0.1-10.0) - Optional ATR bands visualization - Optional ATR histogram display Entry Signals: - 10 Long entry triggers (crossover signals) - 10 Short entry triggers (crossunder signals) - Individual activation for each signal Exit Settings: Take Profit: - Enable/Disable TP - Type: Percent (0.1-100%) or ATR (0.1-20x) - Percent: 0.1% to 100% gain target - ATR: 0.1 to 20 ATR multipliers Stop Loss: - Enable/Disable SL - Type: Percent (0.1-100%) or ATR (0.1-20x) - Percent: 0.1% to 100% loss limit - ATR: 0.1 to 20 ATR multipliers Time Exit: - 0-1000 bars (0 = disabled) Multi-Trade Settings: - Enable/Disable Pyramiding - Max concurrent trades (1-100) - Equity % per trade (0.1-100%) Daily Limit: - Enable/Disable daily trade limit - Max trades per day (1-1000) Backtesting: - Date range filtering - From/To Year, Month, Day selection 🎨 VISUAL DESIGN Modern, clean interface featuring: - Color-coded levels with transparency: - 📗📕 Yesterday (bright green/red) - 🟢🔴 Today (cyan/magenta) - 🔵🟠 Last Week (blue/orange) - 🟣🔷 Last Month (purple/light blue) - 🟤🟫 Last Year (brown) - Different line styles per timeframe - Compact emoji labels (Y-High, T-Low, W-High, M-Low, Yr-High) - Dynamic info panel showing active settings - Semi-transparent fills for ATR zones ⚡ PERFECT FOR - Breakout trading strategies - Multi-timeframe analysis - Systematic algorithmic trading - Range breakout systems - Support/Resistance trading - Scalping with pyramiding - Day trading with level breaks 📊 BACKTESTING ENGINE Comprehensive backtesting with: - Date range filtering for precise periods - Accurate entry/exit execution - Multiple position management - Detailed performance metrics - Trade-by-trade analysis - Pyramiding simulation 🔔 ALERTS AVAILABLE Set custom alerts for: - Any level breakout (10 different levels) - Crossover and crossunder events - All timeframe combinations - Entry and exit signals - Position management events 🆕 VERSION 40.0 UPDATES - Upgraded to Pine Script v6 - Enhanced compatibility and performance - Improved input system (input.bool, input.int, input.float) - Updated security function (request.security) - Fixed ta.barssince calculations - Optimized strategy.close implementation - Shorter title for TradingView compliance ⚠️ IMPORTANT TECHNICAL NOTES - Uses precise limit/stop prices for TP/SL (not ticks) - Entry price-based calculations (not current close) - Pyramiding controlled via strategy declaration - Daily trade counter resets at midnight - ATR calculated on each bar for consistency - Works best on intraday timeframes for daily levels - Time-based exits use global scope calculations 💡 USAGE TIPS - Start with single signal testing to understand behavior - Use percentage-based exits for consistent risk/reward ratios - Enable daily limit to prevent overtrading volatile days - Combine ATR-based stops with percentage targets - Test different level combinations for your specific asset - Lower pyramiding percentage for safer multi-position trading - Consider market volatility when setting ATR multipliers 📈 STRATEGY LOGIC EXPLANATION The strategy identifies critical support/resistance levels from multiple timeframes (yesterday, today, week, month, year) and generates trading signals when price breaks through these levels. **Entry Logic:** - LONG: Price crosses above selected high/low levels - SHORT: Price crosses below selected high/low levels **Exit Logic:** - Take Profit: Fixed percentage or ATR-based target - Stop Loss: Fixed percentage or ATR-based stop - Time Exit: Maximum bars in position **Position Management:** - Pyramiding allows building multiple positions - Daily limiter prevents excessive trading - Per-trade allocation controls risk per entry 🎓 BEST PRACTICES 1. **Risk Management:** Never risk more than 1-2% per trade 2. **Pyramiding:** Use smaller percentages (0.5-2%) when enabled 3. **Daily Limits:** Set realistic limits based on market volatility 4. **TP/SL Ratio:** Aim for minimum 1:1.5 risk/reward ratio 5. **Backtesting:** Test thoroughly across different market conditions 6. **Timeframes:** Use appropriate timeframes for your trading style 7. **Level Selection:** Choose relevant levels for your asset class 📊 RECOMMENDED SETTINGS **Conservative (Low Risk):** - Pyramiding: Disabled - TP: 5% or 3 ATR - SL: 2% or 1.5 ATR - Daily Limit: 3-5 trades - Signals: Week/Month highs only **Moderate (Balanced):** - Pyramiding: Enabled (max 3) - Per Trade: 2% - TP: 3% or 2.5 ATR - SL: 1.5% or 1 ATR - Daily Limit: 5-10 trades - Signals: Yesterday + Week levels **Aggressive (High Risk):** - Pyramiding: Enabled (max 5) - Per Trade: 1% - TP: 2% or 2 ATR - SL: 1% or 0.75 ATR - Daily Limit: 10-20 trades - Signals: All levels enabled ⚠️ RISK DISCLAIMER This indicator is for educational and informational purposes only. Trading involves substantial risk of loss and is not suitable for every investor. Past performance does not guarantee future results. Always: - Test thoroughly in paper trading first - Use proper risk management - Never risk more than you can afford to lose - Understand the strategy before live trading - Consider transaction costs and slippage - Consult a financial advisor if needed 🔧 TROUBLESHOOTING - **No trades executing:** Check if "Enable Strategy" is ON - **Too many trades:** Reduce signals or enable daily limit - **TP/SL not working:** Verify percentage/ATR settings - **Pyramiding not working:** Check max trades and % per trade - **Labels not showing:** Ensure "Show Labels" is enabled 📞 SUPPORT & FEEDBACK For questions, suggestions, bug reports, or feature requests: - Comment below this indicator - Contact the author through TradingView - Report any issues with specific examples 🌟 FEATURES SUMMARY ✅ Multi-timeframe level detection ✅ Customizable breakout signals ✅ ATR and percentage-based exits ✅ Advanced pyramiding system ✅ Daily trade limiting ✅ Time-based exits ✅ Modern visual design ✅ Comprehensive backtesting ✅ Real-time alerts ✅ Pine Script v6 compatible 📚 VERSION HISTORY - v40.0 - Pine Script v6 upgrade + bug fixes - v39.3 - Fixed TP/SL with limit/stop prices - v39.2 - Entry price-based calculations - v39.1 - Fixed daily trade counter - v39.0 - Pyramiding + daily limiter - v38.0 - Multi-trade capability (100 positions) - v37.0 - ATR-based exits - v36.0 - Backtesting integration - v35.0 - Added yearly levels 🚀 GET STARTED 1. Add indicator to your chart 2. Open settings panel 3. Enable "▶️ Enable Strategy" 4. Select your preferred entry signals 5. Configure TP/SL settings 6. Run backtest on historical data 7. Optimize parameters for your asset 8. Set up alerts for live trading Happy Trading! 🎯💰📈 --- © 2025 Multi-Timeframe High/Low Strategy Pro Built with precision. Tested with care. Trade with confidence.
Strategi Pine Script®
oleh MustangAlgo
Adaptive Cortex Strategy (ACS)Strategy Title: Adaptive Cortex Strategy (ACS) This script is invite-only. Part 1: Philosophy and the Fundamental Problem It Solves Adaptive Cortex Strategy (ACS) is an advanced decision support system designed to dynamically adapt to the ever-changing characteristics of the market. A major weakness of traditional approaches is that while successful in a specific market condition (e.g., a strong trend), they become ineffective when the market changes course (e.g., enters a sideways range). ACS solves this problem by continuously analyzing the market's current "regime" and instantly adapting its decision-making logic accordingly. Its primary goal is to enable the strategy itself to "think" and evolve with the market, without requiring the trader to change their strategy. Part 2: Original Methodology and Proprietary Logic A Note on the Original Methodology and Intellectual Property This algorithm is not based on or copied from any open-source strategy code. The system utilizes the mathematical principles of widely accepted indicators such as ADX, RSI, and Ichimoku as data sources for its analyses. However, the intellectual property and unique value of the algorithm lies in its unique and closed-source architecture that processes, prioritizes, and synthesizes data from these standard tools. The methods used in core components, particularly the adaptive 'Cortex' memory system and statistical 'Forecast' engine, represent a unique set of logic developed from scratch for this script. The parameters, order of operations, and conditional logic are entirely custom-designed. Therefore, the system's performance is a result of its unique design, not a repetition of publicly available code. ACS's power lies not in the individual indicators it uses, but in the unique and proprietary logic layers that process the information from these indicators. 1. Multi-Factor Scoring and Adaptive Weighting: The heart of the methodology is a scoring system that analyzes the market in four main categories: Trend, Support/Resistance, Momentum, and Volume. However, what makes ACS unique is that it dynamically changes the importance it assigns to these categories based on the market regime. Unique Application: Using ADX, DMI, and ATR indicators, the system detects whether the market is in different regimes, such as "Strong Trend" or "High Volatility Squeeze." When it detects a strong trend, it automatically increases the weight of the Trend scores from the Ichimoku and proprietary AMF Trend Engine. When it detects sideways or tightness, it shifts its focus to Support/Resistance zones determined by Dynamic Channels and the author's "Cortex" Memory System. A different approach was added here, inspired by the classic Fibonacci estimation. This "adaptive weighting" ensures that the strategy always focuses its attention on the most appropriate area. 2. Statistical Forecast Engine: ACS goes beyond standard indicators and includes a proprietary forecasting algorithm that measures the probability of a potential price movement's success. Unique Implementation: The system stores the results of past tests (successful bounces/breakouts) at key price levels in a "brain" (memory). At the time of a new test, it compares the current RSI momentum, volume anomalies, and market regime with similar past situations. Based on this comparison, it calculates the probability of the current test being successful as a statistical percentage and adds this percentage to the final score as a "bonus" or "penalty." 3. Walk-Forward Architecture: Markets constantly evolve. ACS continues to learn from the latest market dynamics by resetting its memory at regular intervals (e.g., monthly) through its "Re-Learn Mode," rather than being trapped by old data. This is an advanced approach aimed at ensuring the strategy remains current and effective over the long term. Part 3: Practical Features and User Benefits HOW DOES IT HELP INVESTORS? Customizable Trading Profiles: ACS does not come with a single set of settings. Users can instantly adapt all the algorithm's key periods and decision thresholds to their trading style by selecting one of the pre-configured trading profiles, such as "SCALPING," "INTRADAY TREND," or "SWING TRADE." Additionally, they can further fine-tune the selected profile with "Speed ​​Adjustment." Full Automation Compatibility (JSON): The strategy is equipped with fully configurable JSON-formatted alert messages for buy, sell, and position closing transactions. This makes it possible to establish a fully automated trading system by connecting ACS signals to automation platforms such as 3Commas and PineConnector. Dynamic values ​​such as position size ({{strategy.order.contracts}}) are automatically added to alerts. Advanced and Adaptive Risk Management: Protecting capital is as important as making a profit. ACS offers a multi-layered risk management framework for this purpose: Flexible Position Size: Allows you to set the risk for each trade as a percentage of capital or a fixed dollar amount. Adaptive ATR Stop: The stop-loss level is dynamically expanded or contracted based on current market volatility (the ratio of short-term ATR to long-term ATR). Contingency Mechanisms: Includes safety nets such as "Maximum Drawdown Protection" and the "Praetorian Guard" engine, which detects sudden market shocks. Clear and Comprehensible Dashboard: Transforms dozens of complex data points into an intuitive dashboard that provides critical information such as market trends, major trends, support/resistance zones, and final signals at a glance. Section 4: Disclaimers and Rules Transparency Note: This algorithm uses the mathematical foundations of publicly available indicators such as ADX, ATR, RSI, and Ichimoku. However, ACS's intellectual property and unique value lies in its unique architecture, which combines data from these standard tools, prioritizes it by market trend, and synthesizes it with its proprietary "Cortex" and "Statistical Forecast" engines. Educational Use: IMPORTANT WARNING: The Adaptive Cortex Strategy is a professional decision support and analysis tool. It is NOT a system that promises "guaranteed profits." All trading activities involve the risk of capital loss. Past performance is no guarantee of future results. All signals and analysis generated by this script are for educational purposes only and should not be construed as investment advice. Users are solely responsible for applying their own risk management rules and making their final trading decisions. Strategy Backtest Information Please remember that past performance is not indicative of future results. The published chart and performance report were generated on the 4-hour timeframe of the BTC/USD pair with the following settings: Test Period: January 1, 2016 - November 2, 2025 Default Position Size: 15% of Capital Pyramiding: Closed Commission: 0.0008 Slippage: 2 ticks (Please enter the slippage you used in your own tests) Testing Approach: The published test includes 123 trades and is statistically significant. It is strongly recommended that you test on different assets and timeframes for your own analysis. The default settings are a template and should be adjusted by the user for their own analysis.
Strategi Pine Script®
oleh blntdmn
TrendIsYourFriend Strategy (SPY,IWM,VYM,XLK,SPXL,BTC,GOLD,VT...)Personal disclaimer Don’t trust this strategy. Don’t trust any other model either just because of its author or a backtest curve. Overfitting is an easy trap, and beginners often fall into it. This script isn’t meant to impress you. It’s meant to survive reality. If it does, maybe it will raise questions and you’ll remember it. Legal disclaimer Educational purposes only. Not financial advice. Past performance is not indicative of future results. Strategy description Long-only, trend-based logic with two entry types (trend continuation or excess-move reversion), dynamic stop-losses, and a VIX filter to avoid turbulent markets. Minimal number of parameters with enough trades to support robustness. For backtest, each trade is sized at $10,000 flat (no compounding, to focus on raw model quality and the regularity of its results over time). Fees = $0 (neutral choice, as brokers differ). Slippage = $0, deliberate choice: most entries occur on higher timeframes, and some assets start their history on charts at very low prices, which would otherwise distort results. What makes this script original Beyond a classical trend calculation, both excess-move entries and dynamic stop-loss exits also rely on trend logic. Except for the VIX filter, everything comes from trend functions, with very few parameters. Pre-configurations are fixed in the code, allowing sincere performance tracking across a dozen cases over the medium to long term. Allowed SPY (ARCA) — 2-hour chart: S&P 500 ETF, most liquid equity benchmark IWM (ARCA) — Daily chart: Russell 2000 ETF, US small caps VYM (ARCA) — Daily chart: Vanguard High Dividend Yield ETF XLK (ARCA) — Daily chart: Technology Select Sector SPDR SPXL (ARCA) — Daily chart: 3× leveraged S&P 500 ETF BTCUSD (COINBASE) — 4-hour chart: Bitcoin vs USD GOLD (TVC) — Daily chart: Gold spot price VT (ARCA) — Daily chart: Vanguard Total World Stock ETF PG (NYSE) — Daily chart: Procter & Gamble Co. CQQQ (ARCA) — Daily chart: Invesco China Technology ETF EWC (ARCA) — Daily chart: iShares MSCI Canada ETF EWJ (ARCA) — Daily chart: iShares MSCI Japan ETF How to use and form an opinion on it Works only on the pairs above. Feel free to modify the input parameters (slippage, fees, order size, margins, …) to see how the model behaves under your own conditions Compare it with a simple Buy & Hold (requires an order size of 100% equity). You may also want to look at its time-in-market — the share of time your capital is actually at risk. Finally, let me INSIST on this : let it run live for months before forming an opinion! Share your thoughts in the comments 🚀 if you’d like to discuss its live performance.
Strategi Pine Script®
oleh Email-Trader
6
Robotic-ATM V6.6 Professional🤖 Robotic-ATM V6.6 Pro - Advanced Multi-Indicator Algorithmic Trading Strategy Professional algo system combining 4 proven indicators: R-ATM KISS V5 trend detection, LG_TRSpeed momentum analysis, R-ATM Oscillator scoring, WaveTrend wave analysis. Features 3 signal modes (ALL_IMMEDIATE/ALL_SYNC/PARTIAL_SYNC), advanced risk mgmt with stop-loss/profit targets, daily P&L limits, position controls, and volatility filtering. Real-time dashboard tracks trades, win rate, profit/loss, and drawdown. $300/month subscription, 21-day FREE trial, cancel anytime. 3+3 months free when paying quarterly. Educational purposes only. Past performance doesn't guarantee future results. Trading involves substantial risk. Only trade with capital you can afford to lose. Contact: support@robotic-atm.com | robotic-atm.com | Robotic-ATM Inc.
Strategi Pine Script®
oleh anhalex
Robotic-ATM V6.6.3/IO🤖 Robotic-ATM V6.6 3.3 IO - Advanced Multi-Indicator Algorithmic Trading Strategy Professional algo system combining 4 proven indicators: R-ATM KISS V5 trend detection, LG_TRSpeed momentum analysis, R-ATM Oscillator scoring, WaveTrend wave analysis. Features 3 signal modes (ALL_IMMEDIATE/ALL_SYNC/PARTIAL_SYNC), advanced risk mgmt with stop-loss/profit targets, daily P&L limits, position controls, and volatility filtering. Real-time dashboard tracks trades, win rate, profit/loss, and drawdown. $300/month subscription, 21-day FREE trial, cancel anytime. 3+3 months free when paying quarterly. Educational purposes only. Past performance doesn't guarantee future results. Trading involves substantial risk. Only trade with capital you can afford to lose. Contact: sales@robotic-atm.com | robotic-atm.com | Robotic-ATM Inc.
Strategi Pine Script®
oleh anhalex
Quantum Reversal Engine [ApexLegion]Quantum Reversal Engine STRATEGY OVERVIEW This strategy is constructed using 5 custom analytical filters that analyze different market dimensions - trend structure, momentum expansion, volume confirmation, price action patterns, and reversal detection - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions. Why These Custom Filters Were Independently Developed: This strategy employs five custom-developed analytical filters: 1. Apex Momentum Core (AMC) - Custom oscillator with volatility-scaled deviation calculation Standard oscillators lag momentum shifts by 2-3 bars. Custom calculation designed for momentum analysis 2. Apex Wick Trap (AWT) - Wick dominance analysis for trap detection Existing wick analysis tools don't quantify trap conditions. Uses specific ratios for wick dominance detection 3. Apex Volume Pulse (AVP) - Volume surge validation with participation confirmation Volume indicators typically use simple averages. Uses surge multipliers with participation validation 4. Apex TrendGuard (ATG) - Angle-based trend detection with volatility band integration EMA slope calculations often produce false signals. Uses angle analysis with volatility bands for confirmation 5. Quantum Composite Filter (QCF) - Multi-component scoring and signal generation system Composite scoring designed to filter noise by requiring multiple confirmations before signal activation. Each filter represents mathematical calculations designed to address specific analytical requirements. Framework Operation: The strategy functions as a scoring framework where each filter contributes weighted points based on market conditions. Entry signals are generated when minimum threshold scores are met. Exit management operates through a three-tier system with continued signal strength evaluation determining position holds versus closures at each TP level. Integration Challenge: The core difficulty was creating a scoring system where five independent filters could work together without generating conflicting signals. This required backtesting to determine effective weight distributions. Custom Filter Development: Each of the five filters represents analytical approaches developed through testing and validation: Integration Validation: Each filter underwent individual testing before integration. The composite scoring system required validation to verify that filters complement rather than conflict with each other, resulting in a cohesive analytical framework that was tested during the development period. These filters represent custom-developed components created specifically for this strategy, with each component addressing different analytical requirements through testing and parameter adjustment. Programming Features: Multi-timeframe data handling with backup systems Performance optimization techniques Error handling for live trading scenarios Parameter adaptation based on market conditions Strategy Features: Uses multi-filter confirmation approach Adapts position holding based on continued signal strength Includes analysis tools for trade review and optimization Ongoing Development: The strategy was developed through testing and validation processes during the creation period. COMPONENT EXPLANATION EMA System Uses 8 exponential moving averages (7, 14, 21, 30, 50, 90, 120, 200 periods) for trend identification. Primary signals come from 8/21 EMA crossovers, while longer EMAs provide structural context. EMA 1-4 determine short-term structure, EMA 5-8 provide long-term trend confirmation. Apex Momentum Core (AMC) Built custom oscillator mathematics after testing dozens of momentum calculation methods. Final algorithm uses price deviation from EMA baseline with volatility scaling to reduce lag while maintaining accuracy across different market conditions. Custom momentum oscillator using price deviation from EMA baseline: apxCI = 100 * (source - emaBase) / (sensitivity * sqrt(deviation + 1)) fastLine = EMA(apxCI, smoothing) signalLine = SMA(fastLine, 4) Signals generate when fastLine crosses signalLine at +50/-50 thresholds. This identifies momentum expansion before traditional oscillators. Apex Volume Pulse (AVP) Created volume surge analysis that goes beyond simple averages. Extensive testing determined 1.3x multiplier with participation validation provides reliable confirmation while filtering false volume spikes. Compares current volume to 21-period moving average. Requires 1.3x average volume for signal confirmation. This filters out low-volume moves during quiet periods and confirms breakouts with actual participation. Apex Wick Trap (AWT) Developed proprietary wick trap detection through analysis of failed breakout patterns. Tested various ratio combinations before settling on 60% wick dominance + 20% body limit as effective trap identification parameters. Analyzes candle structure to identify failed breakouts: candleRange = math.max(high - low, 0.00001) candleBody = math.abs(close - open) bodyRatio = candleBody / candleRange upperWick = high - math.max(open, close) lowerWick = math.min(open, close) - low upperWickRatio = upperWick / candleRange lowerWickRatio = lowerWick / candleRange trapWickLong = showAWT and lowerWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close > open trapWickShort = showAWT and upperWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close < open This catches reversals after fake breakouts. Apex TrendGuard (ATG) Built angle-based trend detection after standard EMA crossovers proved insufficient. Combined slope analysis with volatility bands through iterative testing to eliminate false trend signals. EMA slope analysis with volatility bands: Fast EMA (21) vs Slow EMA (55) for trend direction Angle calculation: atan(fast - slow) * 180 / π ATR bands (1.75x multiplier) for breakout confirmation Minimum 25° angle for strong trend classification Core Algorithm Framework 1. Composite Signal Generation calculateCompositeSignals() => // Component Conditions structSignalLong = trapWickLong structSignalShort = trapWickShort momentumLong = amcBuySignal momentumShort = amcSellSignal volumeSpike = volume > volAvg_AVP * volMult_AVP priceStrength_Long = close > open and close > close priceStrength_Short = close < open and close < close rsiMfiComboValue = (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2 reversalTrigger_Long = ta.crossover(rsiMfiComboValue, 50) reversalTrigger_Short = ta.crossunder(rsiMfiComboValue, 50) isEMACrossUp = ta.crossover(emaFast_ATG, emaSlow_ATG) isEMACrossDown = ta.crossunder(emaFast_ATG, emaSlow_ATG) // Enhanced Composite Score Calculation scoreBuy = 0.0 scoreBuy += structSignalLong ? scoreStruct : 0.0 scoreBuy += momentumLong ? scoreMomentum : 0.0 scoreBuy += flashSignal ? weightFlash : 0.0 scoreBuy += blinkSignal ? weightBlink : 0.0 scoreBuy += volumeSpike_AVP ? scoreVolume : 0.0 scoreBuy += priceStrength_Long ? scorePriceAction : 0.0 scoreBuy += reversalTrigger_Long ? scoreReversal : 0.0 scoreBuy += emaAlignment_Bull ? weightTrendAlign : 0.0 scoreBuy += strongUpTrend ? weightTrendAlign : 0.0 scoreBuy += highRisk_Long ? -1.2 : 0.0 scoreBuy += signalGreenDot ? 1.0 : 0.0 scoreBuy += isAMCUp ? 0.8 : 0.0 scoreBuy += isVssBuy ? 1.5 : 0.0 scoreBuy += isEMACrossUp ? 1.0 : 0.0 scoreBuy += signalRedX ? -1.0 : 0.0 scoreSell = 0.0 scoreSell += structSignalShort ? scoreStruct : 0.0 scoreSell += momentumShort ? scoreMomentum : 0.0 scoreSell += flashSignal ? weightFlash : 0.0 scoreSell += blinkSignal ? weightBlink : 0.0 scoreSell += volumeSpike_AVP ? scoreVolume : 0.0 scoreSell += priceStrength_Short ? scorePriceAction : 0.0 scoreSell += reversalTrigger_Short ? scoreReversal : 0.0 scoreSell += emaAlignment_Bear ? weightTrendAlign : 0.0 scoreSell += strongDownTrend ? weightTrendAlign : 0.0 scoreSell += highRisk_Short ? -1.2 : 0.0 scoreSell += signalRedX ? 1.0 : 0.0 scoreSell += isAMCDown ? 0.8 : 0.0 scoreSell += isVssSell ? 1.5 : 0.0 scoreSell += isEMACrossDown ? 1.0 : 0.0 scoreSell += signalGreenDot ? -1.0 : 0.0 compositeBuySignal = enableComposite and scoreBuy >= thresholdCompositeBuy compositeSellSignal = enableComposite and scoreSell >= thresholdCompositeSell if compositeBuySignal and compositeSellSignal compositeBuySignal := false compositeSellSignal := false = calculateCompositeSignals() // Final Entry Signals entryCompositeBuySignal = compositeBuySignal and ta.rising(emaFast_ATG, 2) entryCompositeSellSignal = compositeSellSignal and ta.falling(emaFast_ATG, 2) Calculates weighted scores from independent modules and activates signals only when threshold requirements are met. 2. Smart Exit Hold Evaluation System evaluateSmartHold() => compositeBuyRecentCount = 0 compositeSellRecentCount = 0 for i = 0 to signalLookbackBars - 1 compositeBuyRecentCount += compositeBuySignal ? 1 : 0 compositeSellRecentCount += compositeSellSignal ? 1 : 0 avgVolume = ta.sma(volume, 20) volumeSpike = volume > avgVolume * volMultiplier // MTF Bull/Bear conditions mtf_bull = mtf_emaFast_final > mtf_emaSlow_final mtf_bear = mtf_emaFast_final < mtf_emaSlow_final emaBackupDivergence = math.abs(mtf_emaFast_backup - mtf_emaSlow_backup) / mtf_emaSlow_backup emaBackupStrong = emaBackupDivergence > 0.008 mtfConflict_Long = inLong and mtf_bear and emaBackupStrong mtfConflict_Short = inShort and mtf_bull and emaBackupStrong // Layer 1: ATR-Based Dynamic Threshold (Market Volatility Intelligence) atr_raw = ta.atr(atrLen) atrValue = na(atr_raw) ? close * 0.02 : atr_raw atrRatio = atrValue / close dynamicThreshold = atrRatio > 0.02 ? 1.0 : (atrRatio > 0.01 ? 1.5 : 2.8) // Layer 2: ROI-Conditional Time Intelligence (Selective Pressure) timeMultiplier_Long = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure holdTimer_Long <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base holdTimer_Long <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter 1.3 // Loss positions 17+ bars: +30% stricter timeMultiplier_Short = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure holdTimer_Short <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base holdTimer_Short <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter 1.3 // Loss positions 17+ bars: +30% stricter // Dual-Layer Threshold Calculation baseThreshold_Long = mtfConflict_Long ? dynamicThreshold + 1.0 : dynamicThreshold baseThreshold_Short = mtfConflict_Short ? dynamicThreshold + 1.0 : dynamicThreshold timeAdjustedThreshold_Long = baseThreshold_Long * timeMultiplier_Long timeAdjustedThreshold_Short = baseThreshold_Short * timeMultiplier_Short // Final Smart Hold Decision with Dual-Layer Intelligence smartHold_Long = not mtfConflict_Long and smartScoreLong >= timeAdjustedThreshold_Long and compositeBuyRecentCount >= signalMinCount smartHold_Short = not mtfConflict_Short and smartScoreShort >= timeAdjustedThreshold_Short and compositeSellRecentCount >= signalMinCount = evaluateSmartHold() Evaluates whether to hold positions past TP1/TP2/TP3 levels based on continued signal strength, volume confirmation, and multi-timeframe trend alignment HOW TO USE THE STRATEGY Step 1: Initial Setup Apply strategy to your preferred timeframe (backtested on 15M) Enable "Use Heikin-Ashi Base" for smoother signals in volatile markets "Show EMA Lines" and "Show Ichimoku Cloud" are enabled for visual context Set default quantities to match your risk management (5% equity default) Step 2: Signal Recognition Visual Signal Guide: Visual Signal Guide - Complete Reference: 🔶 Red Diamond: Bearish momentum breakdown - short reversal signal 🔷 Blue Diamond: Strong bullish momentum - long reversal signal 🔵 Blue Dot: Volume-confirmed directional move - trend continuation 🟢 Green Dot: Bullish EMA crossover - trend reversal confirmation 🟠 Orange X: Oversold reversal setup - counter-trend opportunity ❌ Red X: Bearish EMA breakdown - trend reversal warning ✡ Star Uprising: Strong bullish convergence 💥 Ultra Entry: Ultra-rapid downward momentum acceleration ▲ VSS Long: Velocity-based bullish momentum confirmation ▼ VSS Short: Velocity-based bearish momentum confirmation Step 3: Entry Execution For Long Positions: 1. ✅ EMA1 crossed above EMA2 exactly 3 bars ago [ta.crossover(ema1,ema2) ] 2. ✅ Current EMA structure: EMA1 > EMA2 (maintained) 3. ✅ Composite score ≥ 5.0 points (6.5+ for 5-minute timeframes) 4. ✅ Cooldown period completed (no recent stop losses) 5. ✅ Volume spike confirmation (green dot/blue dot signals) 6. ✅ Bullish candle closes above EMA structure For Short Positions: 1. ✅ EMA1 crossed below EMA2 exactly 3 bars ago [ta.crossunder(ema1,ema2) ] 2. ✅ Current EMA structure: EMA1 < EMA2 (maintained) 3. ✅ Composite score ≥ 5.4 points (7.0+ for 5-minute timeframes) 4. ✅ Cooldown period completed (no recent stop losses) 5. ✅ Momentum breakdown (red diamond/red X signals) 6. ✅ Bearish candle closes below EMA structure 🎯 Critical Timing Note: The strategy requires EMA crossover to have occurred 3 bars prior to entry, not at the current bar. This attempts to avoid premature entries and may improve signal reliability. Step 4: Reading Market Context EMA Ribbon Interpretation: All EMAs ascending = Strong uptrend context EMAs 1-3 above EMAs 4-8 = Bullish structure Tight EMA spacing = Low volatility/consolidation Wide EMA spacing = High volatility/trending Ichimoku Cloud Context: Price above cloud = Bullish environment Price below cloud = Bearish environment Cloud color intensity = Momentum strength Thick cloud = Strong support/resistance THE SMART EXIT GRID SYSTEM Smart Exit Grid Approach: The Smart Exit Grid uses dynamic hold evaluation that continuously analyzes market conditions after position entry. This differs from traditional fixed profit targets by adapting exit timing based on real-time signal strength. How Smart Exit Grid System Works The system operates through three evaluation phases: Smart Score Calculation: The smart score calculation aggregates 22 signal components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. MTF analysis provides additional confirmation as a separate validation layer. Signal Stack Management: The per-tick signal accumulation system monitors 22 active signal types with MTF providing trend validation and conflict detection as a separate confirmation layer. Take Profit Progression: Smart Exit Activation: The QRE system activates Smart Exit Grid immediately upon position entry. When strategy.entry() executes, the system initializes monitoring systems designed to track position progress. Upon position opening, holdTimer begins counting, establishing the foundation for subsequent decisions. The Smart Exit Grid starts accumulating signals from entry, with all 22 signal components beginning real-time tracking when the trade opens. The system operates on continuous evaluation where smartScoreLong and smartScoreShort calculate from the first tick after entry. QRE's approach is designed to capture market structure changes, trend deteriorations, or signal pattern shifts that can trigger protective exits even before the first take profit level is reached. This activation creates a proactive position management framework. The 8-candle sliding window starts from entry, meaning that if market conditions change rapidly after entry - due to news events, liquidity shifts, or technical changes - the system can respond within the configured lookback period. TP Markers as Reference Points: The TP1, TP2, and TP3 levels function as reference points rather than mandatory exit triggers. When longTP1Hit or shortTP1Hit conditions activate, they serve as profit confirmation markers that inform the Smart Exit algorithm about achieved reward levels, but don't automatically initiate position closure. These TP markers enhance the Smart Exit decision matrix by providing profit context to ongoing signal evaluation. The system recognizes when positions have achieved target returns, but the actual exit decision remains governed by continuous smart score evaluation and signal stack analysis. TP2 Reached: Enhanced Monitoring TP2 represents significant profit capture with additional monitoring features: This approach is designed to help avoid premature profit-taking during trending conditions. If TP2 is reached but smartScoreLong remains above the dynamic threshold and the 8-candle sliding window shows persistent signals, the position continues holding. If market structure deteriorates before reaching TP2, the Smart Exit can trigger closure based on signal analysis. The visual TP circles that appear when levels are reached serve as performance tracking tools, allowing users to see how frequently entries achieve various profit levels while understanding that actual exit timing depends on market structure analysis. Risk Management Systems: Operating independently from the Smart Exit Grid are two risk management systems: the Trap Wick Detection Protocol and the Stop Loss Mechanism. These systems maintain override authority over other exit logic. The Trap Wick System monitors for conditionBearTrapExit during long positions and conditionBullTrapExit during short positions. When detected, these conditions trigger position closure with state reset, bypassing Smart Exit evaluations. This system recognizes that certain candlestick patterns may indicate reversal risk. Volatility Exit Monitoring: The strategy monitors for isStrongBearCandle combined with conditionBearTrapExit, recognizing when market structure may be shifting. Volume Validation: Before exiting on volatility, the strategy requires volume confirmation: volume > ta.sma(volume, 20) * 1.8. This is designed to filter exits on weak, low-volume movements. The Stop Loss Mechanism operates through multiple triggers including traditional price-based stops (longSLHit, shortSLHit) and early exit conditions based on smart score deterioration combined with negative ROI. The early exit logic activates when smartScoreLong < 1.0 or smartScoreShort < 1.0 while realROI < -0.9%. These risk management systems are designed so that risk scenarios can trigger protective closure with state reset across all 22 signal counters, TP tracking variables, and smart exit states. This architecture - Smart Exit activation, TP markers as navigation tools, and independent risk management - creates a position management system that adapts to market conditions while maintaining risk discipline through dedicated protection protocols. TP3 Reached: Enhanced Protection Once TP3 is hit, the strategy shifts into enhanced monitoring: EMA Structure Monitoring: isEMAStructureDown becomes a primary exit trigger MTF Alignment: The higher timeframe receives increased consideration Wick Trap Priority: conditionBearTrapExit becomes an immediate exit signal Approach Differences: Traditional Fixed Exits: Exit at predetermined levels regardless of market conditions May exit during trend continuation May exit before trend completion Limited adaptation to changing volatility Smart Exit Grid Approach: Adaptive timing based on signal conditions Exits when supporting signals weaken Multi-timeframe validation for trend confirmation Volume confirmation requirements for holds Structural monitoring for trend analysis Dynamic ATR-Based Smart Score Threshold System Market Volatility Adaptive Scoring // Real-time ATR Analysis atr_raw = ta.atr(atrLen) atrValue = na(atr_raw) ? close * 0.02 : atr_raw atrRatio = atrValue / close // Three-Tier Dynamic Threshold Matrix dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold (atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard 2.8) // Low volatility: Higher threshold The market volatility adaptive scoring calculates real-time ATR with a 2% fallback for new markets. The atrRatio represents the relationship between current volatility and price, creating a foundation for threshold adjustment. The three-tier dynamic threshold matrix responds to market conditions by adjusting requirements based on volatility levels: lowering thresholds during high volatility periods above 2% ATR ratio to 1.0 points, maintaining standard requirements at 1.5 points for medium volatility between 1-2%, and raising standards to 2.8 points during low volatility periods below 1%. Profit-Loss Adaptive Management: The system applies different evaluation criteria based on position performance: Winning Positions (realROI ≥ 0%): → timeMultiplier = 1.0 (No additional pressure) → Maintains base threshold requirements → Allows natural progression to TP2/TP3 levels Losing Positions (realROI < 0%): → Progressive time pressure activated → Increasingly strict requirements over time → Faster decision-making on underperforming trades ROI-Adaptive Smart Hold Decision Process: The strategy uses a profit-loss adaptive system: Winning Position Management (ROI ≥ 0%): ✅ Standard threshold requirements maintained ✅ No additional time-based pressure applied ✅ Allows positions to progress toward TP2/TP3 levels ✅ timeMultiplier remains at 1.0 regardless of hold duration Losing Position Management (ROI < 0%): ⚠️ Time-based threshold adjustments activated ⚠️ Progressive increase in required signal strength over time ⚠️ Earlier exit evaluation on underperforming positions ⚠️ timeMultiplier increases from 1.0 → 1.1 → 1.3 based on hold duration Real-Time Monitoring: Monitor Analysis Table → "Smart" filter → "Score" vs "Dynamic Threshold" Winning positions: Evaluation based on signal strength deterioration only Losing positions: Evaluation considers both signal strength and progressive time adjustments Breakeven positions (0% ROI): Treated as winning positions - no time adjustments This approach differentiates between winning and losing positions in the hold evaluation process, requiring higher signal thresholds for extended holding of losing positions while maintaining standard requirements for winning ones. ROI-Conditional Decision Matrix Examples: Scenario 1 - Winning Position in Any Market: Position ROI: +0.8% → timeMultiplier = 1.0 (regardless of hold time) ATR Medium (1.2%) → dynamicThreshold = 1.5 Final Threshold = 1.5 × 1.0 = 1.5 points ✅ Position continues Scenario 2 - Losing Position, Extended Hold: Position ROI: -0.5% → Time pressure activated Hold Time: 20 bars → timeMultiplier = 1.3 ATR Low (0.8%) → dynamicThreshold = 2.8 Final Threshold = 2.8 × 1.3 = 3.64 points ⚡ Enhanced requirements Scenario 3 - Fresh Losing Position: Position ROI: -0.3% → Time pressure activated Hold Time: 5 bars → timeMultiplier = 1.0 (still early) ATR High (2.1%) → dynamicThreshold = 1.0 Final Threshold = 1.0 × 1.0 = 1.0 points 📊 Recovery opportunity Scenario 4 - Breakeven Position: Position ROI: 0.0% → timeMultiplier = 1.0 (no pressure) Hold Time: 15 bars → No time penalty applied Final Threshold = dynamicThreshold only ⚖️ Neutral treatment 🔄8-Candle Sliding Window Signal Rotation System Composite Signal Counting Mechanism // Dynamic Lookback Window (configurable: default 8) signalLookbackBars = input.int(8, "Composite Lookback Bars", minval=1, maxval=50) // Rolling Signal Analysis compositeBuyRecentCount = 0 compositeSellRecentCount = 0 for i = 0 to signalLookbackBars - 1 compositeBuyRecentCount += compositeBuySignal ? 1 : 0 compositeSellRecentCount += compositeSellSignal ? 1 : 0 Candle Flow Example (8-bar window): → ✓ ✓ ✗ ✓ ✗ ✓ ✗ ✓ 🗑️ New Signal Count = 5/8 signals in window Threshold Check: 5 ≥ signalMinCount (2) = HOLD CONFIRMED Signal Decay & Refresh Mechanism // Signal Persistence Tracking if compositeBuyRecentCount >= signalMinCount smartHold_Long = true else smartHold_Long = false The composite signal counting operates through a configurable sliding window. The system maintains rolling counters that scan backward through the specified number of candles. During each evaluation cycle, the algorithm iterates through historical bars, incrementing counters when composite signals are detected. This creates a dynamic signal persistence measurement where recent signal density determines holding decisions. The sliding window rotation functions like a moving conveyor belt where new signals enter while the oldest signals drop off. For example, in an 8-bar window, if 5 out of 8 recent candles showed composite buy signals, and the minimum required count is 2, the system confirms the hold condition. As new bars form, the window slides forward, potentially changing the signal count and triggering exit conditions when signal density falls below the threshold. Signal decay and refresh occur continuously where smartHold_Long remains true only when compositeBuyRecentCount exceeds signalMinCount. When recent signal density drops below the minimum requirement, the system switches to exit mode. Advanced Signal Stack Management - 22-Signal Real-Time Evaluation // Long Position Signal Stacking (calc_on_every_tick=true) if inLong // Primary Reversal Signals if signalRedDiamond: signalCountRedDiamond += 1 // -0.5 points if signalStarUprising: signalCountStarUprising += 1 // +1.5 points if entryUltraShort: signalCountUltra += 1 // -1.0 points // Trend Confirmation Signals if strongUpTrend: trendUpCount_Long += 1 // +1.5 points if emaAlignment_Bull: bullAlignCount_Long += 1 // +1.0 points // Risk Assessment Signals if highRisk_Long: riskCount_Long += 1 // -1.5 points if topZone: tzoneCount_Long += 1 // -0.5 points The per-tick signal accumulation system operates with calc_on_every_tick=true for real-time responsiveness. During long positions, the system monitors primary reversal signals where Red Diamond signals subtract 0.5 points as reversal warnings, Star Uprising adds 1.5 points for continuation signals, and Ultra Short signals deduct 1.0 points as counter-trend warnings. Trend confirmation signals provide weighted scoring where strongUpTrend adds 1.5 points for aligned momentum, emaAlignment_Bull contributes 1.0 point for structural support, and various EMA-based confirmations contribute to the overall score. Risk assessment signals apply negative weighting where highRisk_Long situations subtract 1.5 points, topZone conditions deduct 0.5 points, and other risk factors create defensive scoring adjustments. The smart score calculation aggregates all 22 components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. This score updates continuously, providing the foundation for hold-or-exit decisions. MULTI-TIMEFRAME (MTF) SYSTEM MTF Data Collection The strategy requests higher timeframe data (default 30-minute) for trend confirmation: = request.security(syminfo.tickerid, mtfTimeframe, , lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_off) MTF Watchtower System - Implementation Logic The system employs a timeframe discrimination protocol where currentTFInMinutes is compared against a 30-minute threshold. This creates different operational behavior between timeframes: 📊 Timeframe Testing Results: 30M+ charts: Full MTF confirmation → Tested with full features 15M charts: Local EMA + adjusted parameters → Standard testing baseline 5M charts: Local EMA only → Requires parameter adjustment 1M charts: High noise → Limited testing conducted When the chart timeframe is 30 minutes or above, the strategy activates useMTF = true and requests external MTF data through request.security(). For timeframes below 30 minutes, including your 5-minute setup, the system deliberately uses local EMA calculations to avoid MTF lag and data inconsistencies. The triple-layer data sourcing architecture works as follows: timeframes from 1 minute to 29 minutes rely on chart-based EMA calculations for immediate responsiveness. Timeframes of 30 minutes and above utilize MTF data through the security function, with a backup system that doubles the EMA length (emaLen * 2) if MTF data fails. When MTF data is unavailable or invalid, the system falls back to local EMA as the final safety net. Data validation occurs through a pipeline where mtf_dataValid checks not only for non-null values but also verifies that EMA values are positive above zero. The system tracks data sources through mtf_dataSource which displays "MTF Data" for successful external requests, "Backup EMA" for failed MTF with backup system active, or "Chart EMA" for local calculations. 🔄 MTF Smart Score Caching & Recheck System // Cache Update Decision Logic mtfSmartIntervalSec = input.int(300, "Smart Grid Recheck Interval (sec)") // 5-minute cache canRecheckSmartScore = na(timenow) ? false : (na(lastCheckTime) or (timenow - lastCheckTime) > mtfSmartIntervalSec * 1000) // Cache Management if canRecheckSmartScore lastCheckTime := timenow cachedSmartScoreLong := smartScoreLong // Store current calculation cachedSmartScoreShort := smartScoreShort The performance-optimized caching system addresses the computational intensity of continuous MTF analysis through intelligent interval management. The mtfSmartIntervalSec parameter, defaulting to 300 seconds (5 minutes), determines cache refresh frequency. The system evaluates canRecheckSmartScore by comparing current time against lastCheckTime plus the configured interval. When cache updates trigger, the system stores current calculations in cachedSmartScoreLong and cachedSmartScoreShort, creating stable reference points that reduce excessive MTF requests. This cache management balances computational efficiency with analytical accuracy. The cache versus real-time hybrid system creates a multi-layered decision matrix where immediate signals update every tick for responsive market reaction, cached MTF scores refresh every 5 minutes for stability filtering, dynamic thresholds recalculate every bar for volatility adaptation, and sliding window analysis updates every bar for trend persistence validation. This architecture balances real-time signal detection with multi-timeframe strategic validation, creating adaptive trading intelligence that responds immediately to market changes while maintaining strategic stability through cached analysis and volatility-adjusted decision thresholds. ⚡The Execution Section Deep Dive The execution section represents the culmination of all previous systems – where analysis transforms into action. 🚪 Entry Execution: The Gateway Protocol Primary Entry Validation: Entry isn't just about seeing a signal – it's about passing through multiple security checkpoints, each designed to filter out low-quality opportunities. Stage 1: Signal Confirmation entryCompositeBuySignal must be TRUE for longs entryCompositeSellSignal must be TRUE for shorts Stage 2: Enhanced Entry Validation The strategy employs an "OR" logic system that recognizes different types of market opportunities: Path A - Trend Reversal Entry: When emaTrendReversal_Long triggers, it indicates the market structure is shifting in favor of the trade direction. This isn't just about a single EMA crossing – it represents a change in market momentum that experienced traders recognize as potential high-probability setups. Path B - Momentum Breakout Entry: The strongBullMomentum condition is where QRE identifies accelerating market conditions: Criteria: EMA1 rising for 3+ candles AND EMA2 rising for 2+ candles AND Close > 10-period high This combination captures those explosive moves where the market doesn't just trend – it accelerates, creating momentum-driven opportunities. Path C - Recovery Entry: When previous exit states are clean (no recent stop losses), the strategy permits entry based purely on signal strength. This pathway is designed to help avoid the strategy becoming overly cautious after successful trades. 🛡️ The Priority Exit Matrix: When Rules Collide Not all exit signals are created equal. QRE uses a strict hierarchy that is designed to avoid conflicting signals from causing hesitation: Priority Level 1 - Exception Exits (Immediate Action): Condition: TP3 reached AND Wick Trap detected Action: Immediate exit regardless of other signals Rationale: Historical analysis suggests wick traps at TP3 may indicate potential reversals Priority Level 2 - Structural Breakdown: Condition: TP3 active AND EMA structure deteriorating AND Smart Score insufficient Logic: isEMAStructureDown AND NOT smartHold_Long This represents the strategy recognizing that the underlying market structure that justified the trade is failing. It's like a building inspector identifying structural issues – you don't wait for additional confirmation. Priority Level 3 - Enhanced Volatility Exits: Conditions: TP2 active AND Strong counter-candle AND Wick trap AND Volume spike Logic: Multiple confirmation required to reduce false exits Priority Level 4 - Standard Smart Score Exits: Condition: Any TP level active AND smartHold evaluates to FALSE This is the bread-and-butter exit logic where signal deterioration triggers exit ⚖️ Stop Loss Management: Risk Control Protocol Dual Stop Loss System: QRE provides two stop loss modes that users can select based on their preference: Fixed Mode (Default - useAdaptiveSL = false): Uses predetermined percentage levels regardless of market volatility: - Long SL = entryPrice × (1 - fixedRiskP - slipBuffer) - Short SL = entryPrice × (1 + fixedRiskP + slipBuffer) - Default: 0.6% risk + 0.3% slippage buffer = 0.9% total stop - Consistent and predictable stop loss levels - Recommended for users who prefer stable risk parameters Adaptive Mode (Optional - useAdaptiveSL = true): Dynamic system that adjusts stop loss based on market volatility: - Base Calculation uses ATR (Average True Range) - Long SL = entryPrice × (1 - (ATR × atrMultSL) / entryPrice - slipBuffer) - Short SL = entryPrice × (1 + (ATR × atrMultSL) / entryPrice + slipBuffer) - Automatically widens stops during high volatility periods - Tightens stops during low volatility periods - Advanced users can enable for volatility-adaptive risk management Trend Multiplier Enhancement (Both Modes): When strongUpTrend is detected for long positions, the stop loss receives 1.5x breathing room. Strong trends often have deeper retracements before continuing. This is designed to help avoid the strategy being shaken out of active trades by normal market noise. Mode Selection Guidance: - New Users: Start with Fixed Mode for predictable risk levels - Experienced Users: Consider Adaptive Mode for volatility-responsive stops - Volatile Markets: Adaptive Mode may provide better stop placement - Stable Markets: Fixed Mode often sufficient for consistent risk management Early Exit Conditions: Beyond traditional stop losses, QRE implements "smart stops" that trigger before price-based stops: Early Long Exit: (smartScoreLong < 1.0 OR prev5BearCandles) AND realROI < -0.9% 🔄 State Management: The Memory System Complete State Reset Protocol: When a position closes, QRE doesn't just wipe the slate clean – it performs a methodical reset: TP State Cleanup: All Boolean flags: tp1/tp2/tp3HitBefore → FALSE All Reached flags: tp1/tp2/tp3Reached → FALSE All Active flags: tp1/tp2/tp3HoldActive → FALSE Signal Counter Reset: Every one of the 22 signal counters returns to zero. This is designed to avoid signal "ghosting" where old signals influence new trades. Memory Preservation: While operational states reset, certain information is preserved for learning: killReasonLong/Short: Why did this trade end? lastExitWasTP1/TP2/TP3: What was the exit quality? reEntryCount: How many consecutive re-entries have occurred? 🔄 Re-Entry Logic: The Comeback System Re-Entry Conditions Matrix: QRE implements a re-entry system that recognizes not all exits are created equal: TP-Based Re-Entry (Enabled): Criteria: Previous exit was TP1, TP2, or TP3 Cooldown: Minimal or bypassed entirely Logic: Target-based exits indicate potentially viable market conditions EMA-Based Re-Entry (Conditional): Criteria: Previous exit was EMA-based (structural change) Requirements: Must wait for EMA confirmation in new direction Minimum Wait: 5 candles Advanced Re-Entry Features: When adjustReEntryTargets is enabled, the strategy becomes more aggressive with re-entries: Target Adjustment: TP1 multiplied by reEntryTP1Mult (default 2.0) Stop Adjustment: SL multiplied by reEntrySLMult (default 1.5) Logic: If we're confident enough to re-enter, we should be confident enough to hold for bigger moves Performance Tracking: Strategy tracks re-entry win rate, average ROI, and total performance separately from initial entries for optimization analysis. 📊 Exit Reason Analytics: Learning from Every Trade Kill Reason Tracking: Every exit is categorized and stored: "TP3 Exit–Wick Trap": Exit at target level with wick pattern detection "Smart Exit–EMA Down": Structural breakdown exit "Smart Exit–Volatility": Volatility-based protection exit "Exit Post-TP1/TP2/TP3": Standard smart exit progression "Long SL Exit" / "Short SL Exit": Stop loss exits Performance Differentiation: The strategy tracks performance by exit type, allowing for continuous analysis: TP-based exits: Achieved target levels, analyze for pattern improvement EMA-based exits: Mixed results, analyze for pattern improvement SL-based exits: Learning opportunities, adjust entry criteria Volatility exits: Protective measures, monitor performance 🎛️ Trailing Stop Implementation: Conditional Trailing Activation: Activation Criteria: Position profitable beyond trailingStartPct AND (TP hold active OR re-entry trade) Dynamic Trailing Logic: Unlike simple trailing stops, QRE's implementation considers market context: Trending Markets: Wider trail offsets to avoid whipsaws Volatile Markets: Tighter offsets to protect gains Re-Entry Trades: Enhanced trailing to maximize second-chance opportunities Return-to-Entry Protection: When deactivateOnReturn is enabled, the strategy will close positions that return to entry level after being profitable. This is designed to help avoid the frustration of watching profitable trades turn into losers. 🧠 How It All Works Together The beauty of QRE lies not in any single component, but in how everything integrates: The Entry Decision: Multiple pathways are designed to help identify opportunities while maintaining filtering standards. The Progression System: Each TP level unlocks new protection features, like achieving ranks in a video game. The Exit Matrix: Prioritized decision-making aims to reduce analysis paralysis while providing appropriate responses to different market conditions. The Memory System: Learning from each trade while preventing contamination between separate opportunities. The Re-Entry Logic: Re-entry system that balances opportunity with risk management. This creates a trading system where entry conditions filter for quality, progression systems adapt to changing market conditions, exit priorities handle conflicting signals intelligently, memory systems learn from each trade cycle, and re-entry logic maximizes opportunities while managing risk exposure. 📊 ANALYSIS TABLE INTERPRETATION - ⚙️ Enabling Analysis Mode Navigate to strategy settings → "Testing & Analysis" → Enable "Show Analysis Table". The Analysis Table displays different information based on the selected test filter and provides real-time insight into all strategy components, helping users understand current market conditions, position status, and system decision-making processes. 📋 Filter Mode Interpretations "All" Mode (Default View): Composite Section: Buy Score: Aggregated strength from all 22 bullish signals (threshold 5.0+ triggers entry consideration) Sell Score: Aggregated strength from all 22 bearish signals (threshold 5.4+ triggers entry consideration) APEX Filters: ATG Trend: Shows current trend direction analysis Indicates whether momentum filters are aligned for directional bias ReEntry Section: Most Recent Exit: Displays exit type and timeframe since last position closure Status: Shows if ReEntry system is Ready/Waiting/Disabled Count: Current re-entry attempts versus maximum allowed attempts Position Section (When Active): Status: Current position state (LONG/SHORT/FLAT) ROI: Dual calculation showing Custom vs Real ROI percentages Entry Price: Original position entry level Current Price: Live market price for comparison TP Tracking: Progress toward profit targets "Smart" Filter (Critical for Active Positions): Smart Exit Section: Hold Timer: Time elapsed since position opened (bar-based counting) Status: Whether Smart Exit Grid is Enabled/Disabled Score: Current smart score calculation from 22-component matrix Dynamic Threshold: ATR-based minimum score required for holding Final Threshold: Time and ROI-adjusted threshold actually used for decisions Score Check: Pass/Fail based on Score vs Final Threshold comparison Smart Hold: Current hold decision status Final Hold: Final recommendation based on all factors 🎯 Advanced Smart Exit Debugging - ROI & Time-Based Threshold System Understanding the Multi-Layer Threshold System: Layer 1: Dynamic Threshold (ATR-Based) atrRatio = ATR / close dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold (atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard 2.8) // Low volatility: Higher threshold Layer 2: Time Multiplier (ROI & Duration-Based) Winning Positions (ROI ≥ 0%): → timeMultiplier = 1.0 (No time pressure, regardless of hold duration) Losing Positions (ROI < 0%): → holdTimer ≤ 8 bars: timeMultiplier = 1.0 (Early stage, standard requirements) → holdTimer 9-16 bars: timeMultiplier = 1.1 (10% stricter requirements) → holdTimer 17+ bars: timeMultiplier = 1.3 (30% stricter requirements) Layer 3: Final Threshold Calculation finalThreshold = dynamicThreshold × timeMultiplier Examples: - Winning Position: 2.8 × 1.0 = 2.8 (Always standard) - Losing Position (Early): 2.8 × 1.0 = 2.8 (Same as winning initially) - Losing Position (Extended): 2.8 × 1.3 = 3.64 (Much stricter) Real-Time Debugging Display: Smart Exit Section shows: Score: 3.5 → Current smartScoreLong/Short value Dynamic Threshold: 2.8 → Base ATR-calculated threshold Final Threshold: 3.64 (ATR×1.3) → Actual threshold used for decisions Score Check: FAIL (3.5 vs 3.64) → Pass/Fail based on final comparison Final Hold: NO HOLD → Actual system decision Position Status Indicators: Winner + Early: ATR×1.0 (No pressure) Winner + Extended: ATR×1.0 (No pressure - winners can run indefinitely) Loser + Early: ATR×1.0 (Recovery opportunity) Loser + Extended: ATR×1.1 or ATR×1.3 (Increasing pressure to exit) MTF Section: Data Source: Shows whether using MTF Data/EMA Backup/Local EMA Timeframe: Configured watchtower timeframe setting Data Valid: Confirms successful MTF data retrieval status Trend Signal: Higher timeframe directional bias analysis Close Price: MTF price data availability confirmation "Composite" Filter: Composite Section: Buy Score: Real-time weighted scoring from multiple indicators Sell Score: Opposing directional signal strength Threshold: Minimum scores required for signal activation Components: Flash/Blink: Momentum acceleration indicators (F = Flash active, B = Blink active) Individual filter contributions showing which specific signals are firing "ReEntry" Filter: ReEntry System: System: Shows if re-entry feature is Enabled/Disabled Eligibility: Conditions for new entries in each direction Performance: Success metrics of re-entry attempts when enabled 🎯 Key Status Indicators Status Column Symbols: ✓ = Condition met / System active / Signal valid ✗ = Condition not met / System inactive / No signal ⏳ = Cooldown active (waiting period) ✅ = Ready state / Good condition 🔄 = Processing / Transitioning state 🔍 Critical Reading Guidelines For Active Positions - Smart Exit Priority Reading: 1. First Check Position Type: ROI ≥ 0% = Winning Position (Standard requirements) ROI < 0% = Losing Position (Progressive requirements) 2. Check Hold Duration: Early Stage (≤8 bars): Standard multiplier regardless of ROI Extended Stage (9-16 bars): Slight pressure on losing positions Long Stage (17+ bars): Strong pressure on losing positions 3. Score vs Final Threshold Analysis: Score ≥ Final Threshold = HOLD (Continue position) Score < Final Threshold = EXIT (Close position) Watch for timeMultiplier changes as position duration increases 4. Understanding "Why No Hold?" Common scenarios when Score Check shows FAIL: Losing position held too long (timeMultiplier increased to 1.1 or 1.3) Low volatility period (dynamic threshold raised to 2.8) Signal deterioration (smart score dropped below required level) MTF conflict (higher timeframe opposing position direction) For Entry Signal Analysis: Composite Score Reading: Signal strength relative to threshold requirements Component Analysis: Individual filter contributions to overall score EMA Structure: Confirm 3-bar crossover requirement met Cooldown Status: Ensure sufficient time passed since last exit For ReEntry Opportunities (when enabled): System Status: Availability and eligibility for re-engagement Exit Type Analysis: TP-based exits enable immediate re-entry, SL-based exits require cooldown Condition Monitoring: Requirements for potential re-entry signals Debugging Common Issues: Issue: "Score is high but no hold?" → Check Final Threshold vs Score (not Dynamic Threshold) → Losing position may have increased timeMultiplier → Extended hold duration applying pressure Issue: "Why different thresholds for same score?" → Position ROI status affects multiplier → Time elapsed since entry affects multiplier → Market volatility affects base threshold Issue: "MTF conflicts with local signals?" → Higher timeframe trend opposing position → System designed to exit on MTF conflicts → Check MTF Data Valid status ⚡ Performance Optimization Notes For Better Performance: Analysis table updates may impact performance on some devices Use specific filters rather than "All" mode for focused monitoring Consider disabling during live trading for optimal chart performance Enable only when needed for debugging or analysis Strategic Usage: Monitor "Smart" filter when positions are active for exit timing decisions Use "Composite" filter during setup phases for signal strength analysis Reference "ReEntry" filter after position closures for re-engagement opportunities Track Final Threshold changes to understand exit pressure evolution Advanced Debugging Workflow: Position Entry Analysis: Check Composite score vs threshold Verify EMA crossover timing (3 bars prior) Confirm cooldown completion Hold Decision Monitoring: Track Score vs Final Threshold progression Monitor timeMultiplier changes over time Watch for MTF conflicts Exit Timing Analysis: Identify which threshold layer caused exit Track performance by exit type Analyze re-entry eligibility This analysis system provides transparency into strategy decision-making processes, allowing users to understand how signals are generated and positions are managed according to the programmed logic during various market conditions and position states. SIGNAL TYPES AND CHARACTERISTICS 🔥 Core Momentum Signals Flash Signal Calculation: ta.rma(math.abs(close - close ), 5) > ta.sma(math.abs(close - close ), 7) Purpose: Detects sudden price acceleration using smoothed momentum comparison Characteristics: Triggers when recent price movement exceeds historical average movement Usage: Primary momentum confirmation across multiple composite calculations Weight: 1.3 points in composite scoring Blink Signal Calculation: math.abs(ta.change(close, 1)) > ta.sma(math.abs(ta.change(close, 1)), 5) Purpose: Identifies immediate price velocity spikes Characteristics: More sensitive than Flash, captures single-bar momentum bursts Usage: Secondary momentum confirmation, often paired with Flash Weight: 1.3 points in composite scoring ⚡ Advanced Composite Signals Apex Pulse Signal Calculation: apexAngleValue > 30 or apexAngleValue < -30 Purpose: Detects extreme EMA angle momentum Characteristics: Identifies when trend angle exceeds ±30 degrees Usage: Confirms directional momentum strength in trend-following scenarios Pressure Surge Signal Calculation: volSpike_AVP and strongTrendUp_ATG Purpose: Combines volume expansion with trend confirmation Characteristics: Requires both volume spike and strong uptrend simultaneously Usage: bullish signal for trend continuation Shift Wick Signal Calculation: ta.crossunder(ema1, ema2) and isWickTrapDetected and directionFlip Purpose: Detects bearish reversal with wick trap confirmation Characteristics: Combines EMA crossunder with upper wick dominance and directional flip Usage: Reversal signal for trend change identification 🛡️ Trap Exit Protection Signals Bear Trap Exit Calculation: isUpperWickTrap and isBearEngulfNow Conditions: Previous bullish candle with 80%+ upper wick, followed by current bearish engulfing Purpose: Emergency exit signal for long positions Priority: Highest - overrides all other hold conditions Action: Immediate position closure with full state reset Bull Trap Exit Calculation: isLowerWickTrap and isBullEngulfNow Conditions: Previous bearish candle with 80%+ lower wick, followed by current bullish engulfing Purpose: Emergency exit signal for short positions Priority: Highest - overrides all other hold conditions Action: Immediate position closure with full state reset 📊 Technical Analysis Foundation Signals RSI-MFI Hybrid System Base Calculation: (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2 Oversold Threshold: < 35 Overbought Threshold: > 65 Weak Condition: < 35 and declining Strong Condition: > 65 and rising Usage: Momentum confirmation and reversal identification ADX-DMI Trend Classification Strong Up Trend: (adx > 25 and diplus > diminus and (diplus - diminus) > 5) or (ema1 > ema2 and ema2 > ema3 and ta.rising(ema2, 3)) Strong Down Trend: (adx > 20 and diminus > diplus - 5) or (ema1 < ema2 and ta.falling(ema1, 3)) Trend Weakening: adx < adx and adx < adx Usage: Primary trend direction confirmation Bollinger Band Squeeze Detection Calculation: bbWidth < ta.lowest(bbWidth, 20) * 1.2 Purpose: Identifies low volatility periods before breakouts Usage: Entry filter - avoids trades during consolidation 🎨 Visual Signal Indicators Red X Signal Calculation: isBearCandle and ta.crossunder(ema1, ema2) Visual: Red X above price Purpose: Bearish EMA crossunder with confirming candle Composite Weight: +1.0 for short positions, -1.0 for long positions Characteristics: Simple but effective trend change indicator Green Dot Signal Calculation: isBullCandle and ta.crossover(ema1, ema2) Visual: Green dot below price Purpose: Bullish EMA crossover with confirming candle Composite Weight: +1.0 for long positions, -1.0 for short positions Characteristics: Entry confirmation for trend-following strategies Blue Diamond Signal Trigger Conditions: amcBuySignal and score >= 4 Scoring Components: 11 different technical conditions Key Requirements: AMC bullish + momentum rise + EMA expansion + volume confirmation Visual: Blue diamond below price Purpose: Bullish reversal or continuation signal Characteristics: Multi-factor confirmation requiring 4+ technical alignments Red Diamond Signal Trigger Conditions: amcSellSignal and score >= 5 Scoring Components: 11 different technical conditions (stricter than Blue Diamond) Key Requirements: AMC bearish + momentum crash + EMA compression + volume decline Visual: Red diamond above price Purpose: Potential bearish reversal or continuation signal Characteristics: Requires higher threshold (5 vs 4) for more selective triggering 🔵 Specialized Detection Signals Blue Dot Signal Calculation: volumePulse and isCandleStrong and volIsHigh Requirements: Volume > 2.0x MA, strong candle body > 35% of range, volume MA > 55 Purpose: Volume-confirmed momentum signal Visual: Blue dot above price Characteristics: Volume-centric signal for high-liquidity environments Orange X Signal Calculation: Complex multi-factor oversold reversal detection Requirements: AMC oversold + wick trap + flash/blink + RSI-MFI oversold + bullish flip Purpose: Oversold bounce signal with multiple confirmations Visual: Orange X below price Characteristics: Reversal signal requiring 5+ simultaneous conditions VSS (Velocity Signal System) Components: Volume spike + EMA angle + trend direction Buy Signal: vssTrigger and vssTrendDir == 1 Sell Signal: vssTrigger and vssTrendDir == -1 Visual: Green/Red triangles Purpose: Velocity-based momentum detection Characteristics: Fast-response signal for momentum trading ⭐ Elite Composite Signals Star Uprising Signal Base Requirements: entryCompositeBuySignal and echoBodyLong and strongUpTrend and isAMCUp Additional Confirmations: RSI hybrid strong + not high risk Special Conditions: At bottom zone OR RSI bottom bounce OR strong volume bounce Visual: Star symbol below price Purpose: Bullish reversal signal from oversold conditions Characteristics: Most selective bullish signal requiring multiple confirmations Ultra Short Signal Scoring System: 7-component scoring requiring 4+ points Key Components: EMA trap + volume decline + RSI weakness + composite confirmation Additional Requirements: Falling EMA structure + volume spike + flash confirmation Visual: Explosion emoji above price Purpose: Aggressive short entry for trend reversal or continuation Characteristics: Complex multi-layered signal for experienced short selling 🎯 Composite Signal Architecture Enhanced Composite Scoring Long Composite: 15+ weighted components including structure, momentum, flash/blink, volume, price action, reversal triggers, trend alignment Short Composite: Mirror structure with bearish bias Threshold: 5.0 points required for signal activation Conflict Resolution: If both long and short signals trigger simultaneously, both are disabled Final Validation: Requires EMA momentum confirmation (ta.rising(emaFast_ATG, 2) for longs, ta.falling(emaFast_ATG, 2) for shorts) Risk Assessment Integration High Risk Long: RSI > 70 OR close > upper Bollinger Band 80% High Risk Short: RSI < 30 OR close < lower Bollinger Band 80% Zone Analysis: Top zone (95% of 50-bar high) vs Bottom zone (105% of 50-bar low) Risk Penalty: High risk conditions subtract 1.5 points from composite scores This signal architecture creates a multi-layered detection system where simple momentum signals provide foundation, technical analysis adds structure, visual indicators offer clarity, specialized detectors capture different market conditions, and composite signals identify potential opportunities while integrated risk assessment is designed to filter risky entries. VISUAL FEATURES SHOWCASE Ichimoku Cloud Visualization Dynamic Color Intensity: Cloud transparency adapts to momentum strength - darker colors indicate stronger directional moves, while lighter transparency shows weakening momentum phases. Gradient Color Mapping: Bullish momentum renders blue-purple spectrum with increasing opacity, while bearish momentum displays corresponding color gradients with intensity-based transparency. Real-time Momentum Feedback: Color saturation provides immediate visual feedback on market structure strength, allowing traders to assess levels at a glance without additional indicators. EMA Ribbon Bands The 8-level exponential moving average system creates a comprehensive trend structure map with gradient color coding. Signal Type Visualization STRATEGY PROPERTIES & BACKTESTING DISCLOSURE 📊 Default Strategy Configuration: ✅ Initial Capital: 100,000 USD (realistic for average traders) ✅ Commission: 0.075% per trade (realistic exchange fees) ✅ Slippage: 3 ticks (market impact consideration) ✅ Position Size: 5% equity per trade (sustainable risk level) ✅ Pyramiding: Disabled (single position management) ✅ Sample Size: 185 trades over 12-month backtesting period ✅ Risk Management: Adaptive stop loss with maximum 1% risk per trade COMPREHENSIVE BACKTESTING RESULTS Testing Period & Market Conditions: Backtesting Period: June 25, 2024 - June 25, 2025 (12 months) Timeframe: 15-minute charts (MTF system active) Market: BTCUSDT (Bitcoin/Tether) Market Conditions: Full market cycle including volatility periods Deep Backtesting: Enabled for maximum accuracy 📈 Performance Summary: Total Return: +2.19% (+2,193.59 USDT) Total Trades Executed: 185 trades Win Rate: 34.05% (63 winning trades out of 185) Profit Factor: 1.295 (gross profit ÷ gross loss) Maximum Drawdown: 0.65% (653.17 USDT) Risk-Adjusted Returns: Consistent with conservative risk management approach 📊 Detailed Trade Analysis: Position Distribution: Long Positions: 109 trades (58.9%) | Win Rate: 36.70% Short Positions: 76 trades (41.1%) | Win Rate: 30.26% Average Trade Duration: Optimized for 15-minute timeframe efficiency Profitability Metrics: Average Profit per Trade: 11.74 USDT (0.23%) Average Winning Trade: 151.17 USDT (3.00%) Average Losing Trade: 60.27 USDT (1.20%) Win/Loss Ratio: 2.508 (winners are 2.5x larger than losses) Largest Single Win: 436.02 USDT (8.69%) Largest Single Loss: 107.41 USDT (controlled risk management) 💰 Financial Performance Breakdown: Gross Profit: 9,523.93 USDT (9.52% of capital) Gross Loss: 7,352.48 USDT (7.35% of capital) Net Profit After Costs: 2,171.44 USDT (2.17%) Commission Costs: 1,402.47 USDT (realistic trading expenses) Maximum Equity Run-up: 2,431.66 USDT (2.38%) ⚖️ Risk Management Validation: Maximum Drawdown: 0.65% showing controlled risk management Drawdown Recovery: Consistent equity curve progression Risk per Trade: Successfully maintained below 1.5% per position Position Sizing: 5% equity allocation proved sustainable throughout testing period 📋 Strategy Performance Characteristics: ✅ Strengths Demonstrated: Controlled Risk: Maximum drawdown well below industry standards (< 1%) Positive Expectancy: Win/loss ratio of 2.5+ creates profitable edge Consistent Performance: Steady equity curve without extreme volatility Realistic Costs: Includes actual commission and slippage impacts Sample Size: 185 trades during testing period ⚠️ Performance Considerations: Win Rate: 34% win rate requires discipline to follow system signals Market Dependency: Performance may vary significantly in different market conditions Timeframe Sensitivity: Optimized for 15-minute charts; other timeframes may show different results Slippage Impact: Real trading conditions may affect actual performance 📊 Benchmark Comparison: Strategy Return: +2.19% over 12 months Buy & Hold Bitcoin: +71.12% over same period Strategy Advantage: Significantly lower drawdown and volatility Risk-Adjusted Performance: Different risk profile compared to holding cryptocurrency 🎯 Real-World Application Insights: Expected Trading Frequency: Average: 15.4 trades per month (185 trades ÷ 12 months) Weekly Frequency: Approximately 3-4 trades per week Active Management: Requires regular monitoring during market hours Capital Requirements: Minimum Used in Testing: $10,000 for sustainable position sizing Tested Range: $50,000-$100,000 for comfortable risk management Commission Impact: 0.075% per trade totaled 1.4% of capital over 12 months ⚠️ IMPORTANT BACKTESTING DISCLAIMERS: 📈 Performance Reality: Past performance does not guarantee future results. Backtesting results represent hypothetical performance and may not reflect actual trading outcomes due to market changes, execution differences, and emotional factors. 🔄 Market Condition Dependency: This strategy's performance during the tested period may not be representative of performance in different market conditions, volatility regimes, or trending vs. sideways markets. 💸 Cost Considerations: Actual trading costs may vary based on broker selection, market conditions, and trade size. Commission rates and slippage assumptions may differ from real-world execution. 🎯 Realistic Expectations: The 34% win rate requires psychological discipline to continue following signals during losing streaks. Risk management and position sizing are critical for replicating these results. ⚡ Technology Dependencies: Strategy performance assumes reliable internet connection, platform stability, and timely signal execution. Technical failures may impact actual results. CONFIGURATION OPTIMIZATION 5-Minute Timeframe Optimization (Advanced Users Only) ⚠️ Important Warning: 5-minute timeframes operate without MTF confirmation, resulting in reduced signal quality and higher false signal rates. Example 5-Minute Parameters: Composite Thresholds: Long 6.5, Short 7.0 (vs 15M default 5.0/5.4) Signal Lookback Bars: 12 (vs 15M default 8) Volume Multiplier: 2.2 (vs 15M default 1.8) MTF Timeframe: Disabled (automatic below 30M) Risk Management Adjustments: Position Size: Reduce to 3% (vs 5% default) TP1: 0.8%, TP2: 1.2%, TP3: 2.0% (tighter targets) SL: 0.8% (tighter stop loss) Cooldown Minutes: 8 (vs 5 default) Usage Notes for 5-Minute Trading: - Wait for higher composite scores before entry - Require stronger volume confirmation - Monitor EMA structure more closely 15-Minute Scalping Setup: TP1: 1.0%, TP2: 1.5%, TP3: 2.5% Composite Threshold: 5.0 (higher filtering) TP ATR Multiplier: 7.0 SL ATR Multiplier: 2.5 Volume Multiplier: 1.8 (requires stronger confirmation) Hold Time: 2 bars minimum 3-Hour Swing Setup: TP1: 2.0%, TP2: 4.0%, TP3: 8.0% Composite Threshold: 4.5 (more signals) TP ATR Multiplier: 8.0 SL ATR Multiplier: 3.2 Volume Multiplier: 1.2 Hold Time: 6 bars minimum Market-Specific Adjustments High Volatility Periods: Increase ATR multipliers (TP: 2.0x, SL: 1.2x) Raise composite thresholds (+0.5 points) Reduce position size Enable cooldown periods Low Volatility Periods: Decrease ATR multipliers (TP: 1.2x, SL: 0.8x) Lower composite thresholds (-0.3 points) Standard position sizing Disable extended cooldowns News Events: Temporarily disable strategy 30 minutes before major releases Increase volume requirements (2.0x multiplier) Reduce position sizes by 50% Monitor for unusual price action RISK MANAGEMENT Dual ROI System: Adaptive vs Fixed Mode Adaptive RR Mode: Uses ATR (Average True Range) for automatic adjustment TP1: 1.0x ATR from entry price TP2: 1.5x ATR from entry price TP3: 2.0x ATR from entry price Stop Loss: 1.0x ATR from entry price Automatically adjusts to market volatility Fixed Percentage Mode: Uses predetermined percentage levels TP1: 1.0% (default) TP2: 1.5% (default) TP3: 2.5% (default) Stop Loss: 0.9% total (0.6% risk tolerance + 0.3% slippage buffer)(default) Consistent levels regardless of volatility Mode Selection: Enable "Use Adaptive RR" for ATR-based targets, disable for fixed percentages. Adaptive mode works better in varying volatility conditions, while fixed mode provides predictable risk/reward ratios. Stop Loss Management In Adaptive SL Mode: Automatically scales with market volatility Tight stops during low volatility (smaller ATR) Wider stops during high volatility (larger ATR) Include 0.3% slippage buffer in both modes In Fixed Mode: Consistent percentage-based stops 2% for crypto, 1.5% for forex, 1% for stocks Manual adjustment needed for different market conditions Trailing Stop System Configuration: Enable Trailing: Activates dynamic stop loss adjustment Start Trailing %: Profit level to begin trailing (default 1.0%) Trailing Offset %: Distance from current price (default 0.5%) Close if Return to Entry: Optional immediate exit if price returns to entry level Operation: Once position reaches trailing start level, stop loss automatically adjusts upward (longs) or downward (shorts) maintaining the offset distance from favorable price movement. Timeframe-Specific Risk Considerations 15-Minute and Above (Tested): ✅ Full MTF system active ✅ Standard risk parameters apply ✅ Backtested performance metrics valid ✅ Standard position sizing (5%) 5-Minute Timeframes (Advanced Only): ⚠️ MTF system inactive - local signals only ⚠️ Higher false signal rate expected ⚠️ Reduced position sizing preferred (3%) ⚠️ Tighter stop losses required (0.8% vs 1.2%) ⚠️ Requires parameter optimization ⚠️ Monitor performance closely 1-Minute Timeframes (Limited Testing): ❌ Excessive noise levels ❌ Strategy not optimized for this frequency Risk Management Practices Allocate no more than 5% of your total investment portfolio to high-risk trading Never trade with funds you cannot afford to lose Thoroughly backtest and validate the strategy with small amounts before full implementation Always maintain proper risk management and stop-loss settings IMPORTANT DISCLAIMERS Performance Disclaimer Past performance does not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice. Market Risk Cryptocurrency and forex markets are highly volatile. Prices can move rapidly against positions, resulting in significant losses. Users should never risk more than they can afford to lose. Strategy Limitations This strategy relies on technical analysis and may not perform well during fundamental market shifts, news events, or unprecedented market conditions. No trading strategy can guarantee 100% success or eliminate the risk of loss. Legal Compliance You are responsible for compliance with all applicable regulations and laws in your jurisdiction. Consult with licensed financial professionals when necessary. User Responsibility Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
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