The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
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Machine Learning: SuperTrend Strategy TP/SL [YinYangAlgorithms]The SuperTrend is a very useful Indicator to display when trends have shifted based on the Average True Range (ATR). Its underlying ideology is to calculate the ATR using a fixed length and then multiply it by a factor to calculate the SuperTrend +/-. When the close crosses the SuperTrend it changes direction.
This Strategy features the Traditional SuperTrend Calculations with Machine Learning (ML) and Take Profit / Stop Loss applied to it. Using ML on the SuperTrend allows for the ability to sort data from previous SuperTrend calculations. We can filter the data so only previous SuperTrends that follow the same direction and are within the distance bounds of our k-Nearest Neighbour (KNN) will be added and then averaged. This average can either be achieved using a Mean or with an Exponential calculation which puts added weight on the initial source. Take Profits and Stop Losses are then added to the ML SuperTrend so it may capitalize on Momentum changes meanwhile remaining in the Trend during consolidation.
By applying Machine Learning logic and adding a Take Profit and Stop Loss to the Traditional SuperTrend, we may enhance its underlying calculations with potential to withhold the trend better. The main purpose of this Strategy is to minimize losses and false trend changes while maximizing gains. This may be achieved by quick reversals of trends where strategic small losses are taken before a large trend occurs with hopes of potentially occurring large gain. Due to this logic, the Win/Loss ratio of this Strategy may be quite poor as it may take many small marginal losses where there is consolidation. However, it may also take large gains and capitalize on strong momentum movements.
Tutorial:
In this example above, we can get an idea of what the default settings may achieve when there is momentum. It focuses on attempting to hit the Trailing Take Profit which moves in accord with the SuperTrend just with a multiplier added. When momentum occurs it helps push the SuperTrend within it, which on its own may act as a smaller Trailing Take Profit of its own accord.
We’ve highlighted some key points from the last example to better emphasize how it works. As you can see, the White Circle is where profit was taken from the ML SuperTrend simply from it attempting to switch to a Bullish (Buy) Trend. However, that was rejected almost immediately and we went back to our Bearish (Sell) Trend that ended up resulting in our Take Profit being hit (Yellow Circle). This Strategy aims to not only capitalize on the small profits from SuperTrend to SuperTrend but to also capitalize when the Momentum is so strong that the price moves X% away from the SuperTrend and is able to hit the Take Profit location. This Take Profit addition to this Strategy is crucial as momentum may change state shortly after such drastic price movements; and if we were to simply wait for it to come back to the SuperTrend, we may lose out on lots of potential profit.
If you refer to the Yellow Circle in this example, you’ll notice what was talked about in the Summary/Overview above. During periods of consolidation when there is little momentum and price movement and we don’t have any Stop Loss activated, you may see ‘Signal Flashing’. Signal Flashing is when there are Buy and Sell signals that keep switching back and forth. During this time you may be taking small losses. This is a normal part of this Strategy. When a signal has finally been confirmed by Momentum, is when this Strategy shines and may produce the profit you desire.
You may be wondering, what causes these jagged like patterns in the SuperTrend? It's due to the ML logic, and it may be a little confusing, but essentially what is happening is the Fast Moving SuperTrend and the Slow Moving SuperTrend are creating KNN Min and Max distances that are extreme due to (usually) parabolic movement. This causes fewer values to be added to and averaged within the ML and causes less smooth and more exponential drastic movements. This is completely normal, and one of the perks of using k-Nearest Neighbor for ML calculations. If you don’t know, the Min and Max Distance allowed is derived from the most recent(0 index of data array) to KNN Length. So only SuperTrend values that exhibit distances within these Min/Max will be allowed into the average.
Since the KNN ML logic can cause these exponential movements in the SuperTrend, they likewise affect its Take Profit. The Take Profit may benefit from this movement like displayed in the example above which helped it claim profit before then exhibiting upwards movement.
By default our Stop Loss Multiplier is kept quite low at 0.0000025. Keeping it low may help to reduce some Signal Flashing while not taking extra losses more so than not using it at all. However, if we increase it even more to say 0.005 like is shown in the example above. It can really help the trend keep momentum. Please note, although previous results don’t imply future results, at 0.0000025 Stop Loss we are currently exhibiting 69.27% profit while at 0.005 Stop Loss we are exhibiting 33.54% profit. This just goes to show that although there may be less Signal Flashing, it may not result in more profit.
We will conclude our Tutorial here. Hopefully this has given you some insight as to how Machine Learning, combined with Trailing Take Profit and Stop Loss may have positive effects on the SuperTrend when turned into a Strategy.
Settings:
SuperTrend:
ATR Length: ATR Length used to create the Original Supertrend.
Factor: Multiplier used to create the Original Supertrend.
Stop Loss Multiplier: 0 = Don't use Stop Loss. Stop loss can be useful for helping to prevent false signals but also may result in more loss when hit and less profit when switching trends.
Take Profit Multiplier: Take Profits can be useful within the Supertrend Strategy to stop the price reverting all the way to the Stop Loss once it's been profitable.
Machine Learning:
Only Factor Same Trend Direction: Very useful for ensuring that data used in KNN is not manipulated by different SuperTrend Directional data. Please note, it doesn't affect KNN Exponential.
Rationalized Source Type: Should we Rationalize only a specific source, All or None?
Machine Learning Type: Are we using a Simple ML Average, KNN Mean Average, KNN Exponential Average or None?
Machine Learning Smoothing Type: How should we smooth our Fast and Slow ML Datas to be used in our KNN Distance calculation? SMA, EMA or VWMA?
KNN Distance Type: We need to check if distance is within the KNN Min/Max distance, which distance checks are we using.
Machine Learning Length: How far back is our Machine Learning going to keep data for.
k-Nearest Neighbour (KNN) Length: How many k-Nearest Neighbours will we account for?
Fast ML Data Length: What is our Fast ML Length?? This is used with our Slow Length to create our KNN Distance.
Slow ML Data Length: What is our Slow ML Length?? This is used with our Fast Length to create our KNN Distance.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Auto Trailing stoploss By InvestYourAsset💥The Auto Trailing Stop-Loss indicator is a technical indicator that uses the ATR (Average True Range) to calculate a trailing stop-loss for both long and short positions.
💥The signals according to the indicator allows traders to exit from the position before its too late! The indicator can be used to determine when to enter and exit trades.
💥To use the indicator, you simply need to set the input parameters to suit your trading style and risk tolerance. The default values for the parameters are:
p: The ATR period (14)
q: The stop period (20)
x: The multiplier used to calculate the initial high and initial low (1.5)
Calculations:
📈Calculates the ATR using the specified period you can modify ATR period according to your trading style.
📈Calculates the initial high and low stop levels based on the highest high and lowest low over the user defined ATR period.
📈Calculates short and long stoploss levels using the initial high and low stops.
💥Once you have set the input parameters according to your trading style whether you are a day trader or a swing trader, the indicator will plot the short stoploss, long stoploss, and stoploss hit signals on your chart.
💥You can use the indicator to enter and exit trades in a various ways.
For example,
🚀 you could enter a long trade when the price crosses above both red and green lines plotted on the chart. (or when price crosses over both short stoploss and long stoploss.) You could also use the indicator to secure your profits by moving your stop-loss up as the price moves in your favor.
Here is an example of how you could use the indicator to enter and exit trades:
🚀Enter a long trade when the price crosses above the red line or short stoploss.
✅keep Moving your stop-loss upward with the long stoploss or green line.
✅Exit the trade when the price crosses below the long stoploss or green line.
💥You can also use the indicator to protect your existing trades. For example, if you are already in a long trade, you could move your stop-loss up to the short stop when the price moves up 10%. This will help you to protect your profits in case the price starts to move against you.
💥💥some additional tips for using the Auto Trailing Stop-Loss indicator:
✅Use the indicator in conjunction with other technical indicators or your own trading strategy to generate entry and exit signals.
✅Backtest your trading strategy before using it live to make sure that it is profitable.
✅Use the indicator to protect your profits by moving your stop-loss up as the price moves in your favor.
✅ Always follow risk management rules and manage your position sizing according to your risk appetite.
✅ Be aware of the overall trend direction. If the trend is up, you should be looking for bullish reversals or continuations. If the trend is down, you should be looking for bearish reversals or continuations.
This script essentially provides a visual representation of a trading strategy that automatically adjusts stop-loss levels based on market volatility (ATR). It also includes signals for entering long or short positions and visually highlights these signals on the chart.
📣📣Follow us for timely updates regarding future indicators and give it a like if you appreciate the work.📣📣
[dharmatech] KBDR Mean ReversionBased on the criteria described in the book "Mean Revision Trading" by Nishant Pant.
Bullish signal criteria:
Bollinger Bands must be outside Keltner Channel
Price near bottom bband
DI+ increasing
DI- decreasing
RSI near bottom and increasing
Bearish signal criteria:
Bollinger Bands must be outside Keltner Channel
Price near upper bband
DI+ decreasing
DI- increasing
RSI near upper and decreasing
A single triangle indicates that all 4 criteria are met.
If letters appear with the triangle, this indicates that there was a partial criteria match.
K : bbands outside Keltner
B : bbands criteria met
D : DI criteria met
R : RSI criteria met
You can use the settings to turn off partial signals. For example:
"Partial 3" means show signals where 3 of the criteria are met.
If you want more insight into the underlying criteria, load these indicators as well:
Bollinger Bands (built-in to TradingView)
Keltner Channels (built-in to TradingView)
RSI (built-in to TradingView)
ADX and DI
Warning:
Not meant to be used as a stand-alone buy/sell signal.
It regularly provides signals which would not be profitable.
It's meant to be used in conjunction with other analysis.
Think of this as a time-saving tool. Instead of manually checking RSI, DI+/DI-, bbands, distance, etc. this does all of that for you on the fly.
YinYang RSI Volume Trend StrategyThere are many strategies that use RSI or Volume but very few that take advantage of how useful and important the two of them combined are. This strategy uses the Highs and Lows with Volume and RSI weighted calculations on top of them. You may be wondering how much of an impact Volume and RSI can have on the prices; the answer is a lot and we will discuss those with plenty of examples below, but first…
How does this strategy work?
It’s simple really, when the purchase source crosses above the inner low band (red) it creates a Buy or Long. This long has a Trailing Stop Loss band (the outer low band that's also red) that can be adjusted in the Settings. The Stop Loss is based on a % of the inner low band’s price and by default it is 0.1% lower than the inner band’s price. This Stop Loss is not only a stop loss but it can also act as a Purchase Available location.
You can get back into a trade after a stop loss / take profit has been hit when your Reset Purchase Availability After condition has been met. This can either be at Stop Loss, Entry or None.
It is advised to allow it to reset in case the stop loss was a fake out but the call was right. Sometimes it may trigger stop loss multiple times in a row, but you don’t lose much on stop loss and you gain lots when the call is right.
The Take Profit location is the basis line (white). Take Profit occurs when the Exit Source (close, open, high, low or other) crosses the basis line and then on a different bar the Exit Source crosses back over the basis line. For example, if it was a Long and the bar’s Exit Source closed above the basis line, and then 2 bars later its Exit Source closed below the basis line, Take Profit would occur. You can disable Take Profit in Settings, but it is very useful as many times the price will cross the Basis and then correct back rather than making it all the way to the opposing zone.
Longs:
If for instance your Long doesn’t need to Take Profit and instead reaches the top zone, it will close the position when it crosses above the inner top line (green).
Please note you can change the Exit Source too which is what source (close, open, high, low) it uses to end the trades.
The Shorts work the same way as the Long but just opposite, they start when the purchase source crosses under the inner upper band (green).
Shorts:
Shorts take profit when it crosses under the basis line and then crosses back.
Shorts will Stop loss when their outer upper band (green) is crossed with the Exit Source.
Short trades are completed and closed when its Exit Source crosses under the inner low red band.
So, now that you understand how the strategy works, let’s discuss why this strategy works and how it is profitable.
First we will discuss Volume as we deem it plays a much bigger role overall and in our strategy:
As I’m sure many of you know, Volume plays a huge factor in how much something moves, but it also plays a role in the strength of the movement. For instance, let’s look at two scenarios:
Bitcoin’s price goes up $1000 in 1 Day but the Volume was only 10 million
Bitcoin’s price goes up $200 in 1 Day but the Volume was 40 million
If you were to only look at the price, you’d say #1 was more important because the price moved x5 the amount as #2, but once you factor in the volume, you know this is not true. The reason why Volume plays such a huge role in Price movement is because it shows there is a large Limit Order battle going on. It means that both Bears and Bulls believe that price is a good time to Buy and Sell. This creates a strong Support and Resistance price point in this location. If we look at scenario #2, when there is high volume, especially if it is drastically larger than the average volume Bitcoin was displaying recently, what can we decipher from this? Well, the biggest take away is that the Bull’s won the battle, and that likely when that happens we will see bullish movement continuing to happen as most of the Bears Limit Orders have been fulfilled. Whereas with #2, when large price movement happens and Bitcoin goes up $1000 with low volume what can we deduce? The main takeaway is that Bull’s pressured the price up with Market Orders where they purchased the best available price, also what this means is there were very few people who were wanting to sell. This generally dictates that Whale Limit orders for Sells/Shorts are much higher up and theres room for movement, but it also means there is likely a whale that is ready to dump and crash it back down.
You may be wondering, what did this example have to do with YinYang RSI Volume Trend Strategy? Well the reason we’ve discussed this is because we use Volume multiple times to apply multiplications in our calculations to add large weight to the price when there is lots of volume (this is applied both positively and negatively). For instance, if the price drops a little and there is high volume, our strategy will move its bounds MUCH lower than the price actually dropped, and if there was low volume but the price dropped A LOT, our strategy will only move its bounds a little. We believe this reflects higher levels of price accuracy than just price alone based on the examples described above.
Don’t believe us?
Here is with Volume NOT factored in (VWMA = SMA and we remove our Volume Filter calculation):
Which produced -$2880 Profit
Here is with our Volume factored in:
Which produced $553,000 (55.3%)
As you can see, we wen’t from $-2800 profit with volume not factored to $553,000 with volume factored. That's quite a big difference! (Please note previous success does not predict future success we are simply displaying the $ amounts as example).
Now how about RSI and why does it matter in this strategy?
As I’m sure most of you are aware, RSI is one of the leading indicators used in trading. For this reason we figured it would only make sense to incorporate it into our calculations. We fiddled with RSI for quite awhile and sometimes what logically seems to be the right way to use it isn’t. Now, because of this, our RSI calculation is a little odd, but basically what we’re doing is we calculate the RSI, then turn it into a percentage (between 0-1) that can easily be multiplied to the price point we need. The price point we use is the difference between our high purchase zone and our low purchase zone. This allows us to see how much price movement there is between zones. We multiply our zone size with our RSI multiplication and we get the amount we will add +/- to our basis line (white line). This officially creates the NEW high and low purchase zones that we are actually using and displaying in our trades.
If you found that confusing, here are some examples to why it is an important calculation for this strategy:
Before RSI factored in:
Which produced 27.8% Profit
After RSI factored in:
Which produced 553% Profit
As you can see, the RSI makes not only the purchase zones more accurate, but it also greatly increases the profit the strategy is able to make. It also helps ensure an relatively linear profit slope so you know it is reliable with its trades.
This strategy can work on pretty much anything, but you should tweak the values a bit for each pair you are trading it with for best results.
We hope you can find some use out of this simple but effective strategy, if you have any questions, comments or concerns please let us know.
HAPPY TRADING!
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
Binary Option Strategy Tester with Martingale-Basic V.2In Binary options, strategy testing is a bit different. The strategy result depends upon expiry intervals and payout ratio.
My previous script was a try to resolve this but has some bugs in specific choices. The new version overcame those and added some new features useful for binary option strategy testing.
Assumption:
We are opening position at next candle after signal come
Chart interval is option expiry time.
We are taking the position at opening price
Our call will be profitable if we get a green candle and put will be profitable if we get a red candle
We can open only one trade at a time. So if we are in trade, subsequent signals will be ignored.
All Input Options:
Test Call/Put individually or both. Default BOTH
Select up to 5 Martingale levels. Default 2
Type of Martingale Trade. Default “SAME”
“SAME”: If you are trading CALL and incur a loss, you are taking CALL in subsequent Martingale levels.
“OPSITE”: if you are trading CALL and incur a loss, you are taking PUT in subsequent Martingale levels.
“FOLLOW CANDLE COLOR”: You are following candle color in Martingale levels, i.e if the loss candle is RED, you are taking PUT in subsequent candles.
“OPPOSITE CANDLE COLOR”: You are taking opposite candle color trade, i.e if the loss candle is RED, you are taking CALL in subsequent candle.
Select Specific Trading Session. Please select “USE SPECIFIC SESSION”. Default: TRUE
Put the investment amount per option. Default: 10
Payout ratio. Default: 80%
The strategy is taken from Vdub Binary Options SniperVX v1 (by @vdubus). I have deleted extra parts and kept only the necessary parts.
Result Table
Signal and Win Levels:
Signal and Loss:
Please note that Binary options trading is very risky. You must be aware of the risk and be willing to accept them in order to invest in binary options. Only invest what you can afford to lose. The past performance of any trading system, strategy, or methodology is not necessarily indicative of future results.
Powertrend - Volume Range Filter Strategy [wbburgin]The Powertrend is a range filter that is based off of volume, instead of price. This helps the range filter capture trends more accurately than a price-based range filter, because the range filter will update itself from changes in volume instead of changes in price. In certain scenarios this means that the Powertrend will be more profitable than a normal range filter.
Essentials of the Strategy
This is a breakout strategy which works best on trending assets with high volume and liquidity. It should be used on middle to higher timeframes and can be used on all assets that have volume provided by the data source (stocks, crypto, forex). It is long-only as of now. It can work on lower timeframes if you optimize the strategy filters to make less trades or if your exchange/broker is low/no fees, provided that your exchange/broker has high liquidity and volume.
The strategy enters a long position if the range filter is trending upwards and the price crosses over the upper range band, which signifies a price-volume breakout. The strategy closes the long position if the range filter is trending downwards and the price crosses under the lower range band, which signifies a breakdown. Both these conditions can be altered by the three filter options in the settings. The default trend filter is not alterable because it helps prevent false entries and exits that are against the trend.
Settings
The Length setting is the lookback period for the range smoothing.
The ADX Filter setting enables you to turn on an ADX filter, which will halt entries and exits unless the ADX of your customizable length is above a ADX VWMA of that length.
The Range Supertrend setting creates a supertrend from the top and bottom ranges, which can be used to filter entries and exits. The length is customizable. The filter can show you whether the range is making higher highs and lower lows. Below is an example of the Range Supertrend being used as a filter and plotted on-chart:
The VWMA setting halts entries if they are below a customizable length VWMA.
Both the Range Supertrend and the VWMA can also be plotted separately without actually filtering the strategy, so that you can use them independently if you wish. You can turn off the bar color, the highlighting, and the labels if you wish in the settings. A note about the bar color: if the color changes but the strategy does not signal an exit or entry this means that the crossover was against the trend. In these circumstances it may be indicative of a pullback to enter or exit or to add onto your position.
About the Strategy Results Below
A range filter is normally composed of two components - the range filter itself and a smoothing function. In the development of this script I tested both normal and volume-based varieties of the range filter and the smoothing function:
Tests Performed
Volume-based Range x VWMA smoothing
Price-based Range x VWMA smoothing
Price-based Range x EMA smoothing
Volume-based Range x EMA smoothing (final result)
The highest-performing was a volume-based range filter and a normal EMA-based smoothing function, but that does not mean that this strategy will be profitable - exits are based off of signal reversion so I strongly encourage you to develop your own take profits/stop losses for the strategy if you think it may be a good fit for you. The results below are with a commission value of 0.05% (because I built the strategy first for equities), slippage of 3, so if your exchange/broker has a higher fee schedule, I recommend adding filters and/or moving to higher timeframes for the strategy. Additionally, I used 10% of equity in each trade, while using the Range Supertrend filter (the previous upload was unrealistic because it used 100% of equity - missed a 0, apologies, and added in slippage).
[SMT] Buy & Sell Renko Based - AlertsThis is a custom indicator that implements a trading strategy based on Renko charts, but they can be used on regular candlestick charts and on any time frame. Renko charts are known for filtering market noise and displaying price movements in a clearer way. However, it is important to note that this indicator is provided for educational and informational purposes only and is not a guarantee of profitable returns.
Features:
- The indicator uses Renko charts to generate buy and sell signals.
- Renko bricks are built based on a predefined price variation, rather than time.
- The length of the Average True Range (ATR) used to calculate Renko bricks can be customized.
- Buy signals are generated when the price crosses below the current Renko brick.
- Sell signals are generated when the price crosses above the current Renko brick.
- Entry points are marked with "Buy" and "Sell" arrows on the chart.
It is essential to emphasize that no indicator or trading strategy guarantees profitable results. The financial market is complex and subject to unpredictable changes. It is recommended to perform additional tests and analysis before using this indicator on a real trading account.
Always remember to manage your risks properly and consider other factors such as fundamental analysis and market conditions when making trading decisions. The use of this indicator is entirely the user's responsibility.
DISCLAIMER: This indicator is not financial advice and should not be interpreted as such. Always consult with a qualified financial professional before making any investment decisions.
[SMT] Buy & Sell Renko Based - StrategyThis is a custom indicator that implements a trading strategy based on Renko charts, but they can be used on regular candlestick charts and on any time frame. Renko charts are known for filtering market noise and displaying price movements in a clearer way. However, it is important to note that this indicator is provided for educational and informational purposes only and is not a guarantee of profitable returns.
Features:
- The indicator uses Renko charts to generate buy and sell signals.
- Renko bricks are built based on a predefined price variation, rather than time.
- The length of the Average True Range (ATR) used to calculate Renko bricks can be customized.
- Buy signals are generated when the price crosses below the current Renko brick.
- Sell signals are generated when the price crosses above the current Renko brick.
- Entry points are marked with "Buy" and "Sell" arrows on the chart.
It is essential to emphasize that no indicator or trading strategy guarantees profitable results. The financial market is complex and subject to unpredictable changes. It is recommended to perform additional tests and analysis before using this indicator on a real trading account.
Always remember to manage your risks properly and consider other factors such as fundamental analysis and market conditions when making trading decisions. The use of this indicator is entirely the user's responsibility.
DISCLAIMER: This indicator is not financial advice and should not be interpreted as such. Always consult with a qualified financial professional before making any investment decisions.
Strategy Template + Performance & Returns table + ExtrasA script I've been working on since summer 2022. A template for any strategy so you just have to write or paste the code and go straight into risk management settings
Features:
>Signal only Longs/only Shorts/Both
>Leverage system
>Proper fees calculation (even with leverage on)
>Different Stop Loss systems: Simple percentage, 4 different "move to Break Even" systems and Scaling SL after each TP order (read the disclaimer at the bottom regarding this and the TV % profitable metric)
>2 Take Profit systems: Simple percentages, or Risk/reward ratios based on SL level
>Additional option on TP so last one "rides free" until closure of position or Stoploss is hit (for more than 1 orders)
>Up to 5 TP orders
>Show or hide SL/TP levels on demand
>2 date filters. Manual filter is nothing new, enter two dates/hours and filter will turn on. BUT automatic filter is another thing (thanks to user @bfr_ for his help in codingthis feature)
>AUTOMATIC DATE FILTER. Allows you to split all historical data on the chart in X periods, then choose the range of periods used. Up to 10 but that can be changed, instructions included. Useful for WalkForward simulations, haven't seen a script in TradingView that allows you to do this and test your strategy on "unseen data" automatically
EXTRA SETTINGS
Besides, some additions I like to add to my codes:
>Returns table for monthly and weekly performance. Requires recalculation on every tick. This is a modified version of @QuantNomad's work. May add lower TF options later on
>Volume Based S/R system. Original work from @shtcoinr
>One feature that was made by me, the "portfolio table". Yields info and metrics of your strategy, current position and balance. You're able to turn it off and change its size
Should anyone find an error, or have any idea on how to improve this code, please contact me. Future updates could come, stay tuned
DISCLAIMER:
In order to have accurate StopLoss hit, I had to change the previous system, which was a "close position on candle close" instead at actual stoploss level. It was fixed, but resulted on inflation of the number of trading orders, thus reducing the percent profitable and making it strongly biased and unreal. Keep that in mind, that "real" profitability could be 2x or 3x the metric TradingView says. If your strategy has a really high trading frequency, resulting in 3000+ orders, might be a problem. Try to make use of the automatic/manual date filter as workaround, I have no means of changing this, seems it is not a bug but an intended design of the PineScript Code
MTF Diagonally Layered RSI - 1 minute Bitcoin Bot [wbburgin]This is a NON-REPAINTING multi-timeframe RSI strategy (long-only) that enters a trade only when two higher timeframes are oversold. I wrote it on BTC/USD for 1min, but the logic should work on other assets as well. It is diagonally layered to be profitable for when the asset is in a downtrend.
Diagonal layering refers to entry and exit conditions spread across different timeframes. Normally, indicators can become unprofitable because in downtrends, the overbought zones of the current timeframe are not reached. Rather, the overbought zones of the faster timeframes are reached first, and then a selloff occurs. Diagonally-layered strategies mitigate this by selling diagonally, that is, selling once the faster timeframe reaches overbought and buying once the slower timeframe reaches oversold.
Thus this strategy is diagonally layered down . I may create a separate script that alternates between diagonal-up and diagonal-down based off of overall trend, as in extended trend periods up this indicator may not flash as frequently. This can be visualized in a time series x timeframe chart as an "X" shape. Something to consider...
Let me know if you like this strategy. Feel free to alter the pyramiding entries, initial capital, and entry size, as well as commission regime. My strategies are designed to maximize average profit instead of flashing super frequently, as the fees will eat you up. Additionally, at the time of publication, all of my strategy scripts are intended to have profitable Sharpe and Sortino ratios.
Timeframes, RSI period, and oversold/overbought bounds are configurable.
Historical Volatility Scale [ChartPrime]This indicator outputs a visual scale representing the level of volatility in the market relative to the timeframe selected on the users chart. The method of volatility used is "historical volatility" which is calculated by taking the standard deviation of a series of "x" length which contains the current closing price divided by the previous closing price for all nodes. The output of the volatility is standardized by also running an additional percentrank calculation over the raw volatility values to allow the volatility scale to oscillate properly between its minimum of 0 and maximum of 100.
📗 SETTINGS
Length: The length determines how many bars/nodes should be considered when calculating the standard deviation. In simple terms, the higher the length, the less sensitive and less reactive the scale will be to current price action, and larger moves would be required to trigger the scale.
🧰 UTILITY
The arrow or "The Pin" will move upwards towards the "fire" emoji when the volatility is higher than the majority of values for the amount of bars back that you set the "length" setting to. Vise Versa for when the pin is lowering towards the "snooze" emoji, the volatility is less than the majority of nodes/values for the past "length" amount of values.
When the volatility is low, a trader could consider utilizing more leading indicators to make their trading decisions as opposed to lagging indicator such as trend indicators. When the volatility is low, the price action is consolidation which would be bad for a trend following strategy. Vise Versa for trend strategies, having a higher volatility may be better for such strategies.
Its important to remember that this indicator itself is a lagging indicator, in that it relies on historical data to showcase the current state of the markets volatility. This means that although the recommendation in the previous paragraph may make logical sense, it is not a guarantee that if the volatility is showcasing a trending market, that your trend strategies will necessarily be profitable.
Crypto McClellan Oscillator (SLN Fix)This is an adaption of the Mcclellan Oscillator for crypto. Instead of tracking the S&P500 it tracks a selection of cryptos to make sure the indicator follows this sector instead.
Full credit goes to the creator of this indicator: Fadior. It has since been fixed by SLN.
The following description explains the standard McClellan Oscillator. Full credit to Investopedia , my fav source of financial explanations.
The same principles applies to its use in the crypto sector, but please be cautious of the last point, the limitations. Since crypto is more volatile, that could amplify choppy behavior.
This is not financial advice, please be extremely cautious. This indicator is only suitable as a confirmation signal and needs support of other signals to be profitable.
This indicator usually produces the best signals on slightly above daily time frame. I personally like 2 or 3 day, but you have to find the settings suitable for your trading style.
What Is the McClellan Oscillator?
The McClellan Oscillator is a market breadth indicator that is based on the difference between the number of advancing and declining issues on a stock exchange, such as the New York Stock Exchange (NYSE) or NASDAQ.
The indicator is used to show strong shifts in sentiment in the indexes, called breadth thrusts. It also helps in analyzing the strength of an index trend via divergence or confirmation.
The McClellan Oscillator formula can be applied to any stock exchange or group of stocks.
A reading above zero helps confirm a rise in the index, while readings below zero confirm a decline in the index.
When the index is rising but the oscillator is falling, that warns that the index could start declining too. When the index is falling and the oscillator is rising, that indicates the index could start rising soon. This is called divergence.
A significant change, such as moving 100 points or more, from a negative reading to a positive reading is called a breadth thrust. It may indicate a strong reversal from downtrend to uptrend is underway on the stock exchange.
How to Calculate the McClellan Oscillator
To get the calculation started, track Advances - Declines on a stock exchange for 19 and 39 days. Calculate a simple average for these, not exponential moving average (EMA).
Use these simple values as the Prior Day EMA values in the 19- and 39-day EMA formulas.
Calculate the 19- and 39-day EMAs.
Calculate the McClellan Oscillator value.
Now that the value has been calculated, on the next calculation use this value for the Prior Day EMA. Start calculating EMAs for the formula instead of simple averages.
If using the adjusted formula, the steps are the same, except use ANA instead of using Advances - Declines.
What Does the McClellan Oscillator Tell You?
The McClellan Oscillator is an indicator based on market breadth which technical analysts can use in conjunction with other technical tools to determine the overall state of the stock market and assess the strength of its current trend.
Since the indicator is based on all the stocks in an exchange, it is compared to the price movements of indexes that reflect that exchange, or compared to major indexes such as the S&P 500.
Positive and negative values indicate whether more stocks, on average, are advancing or declining. The indicator is positive when the 19-day EMA is above the 39-day EMA, and negative when the 19-day EMA is below the 39-day EMA.
A positive and rising indicator suggests that stocks on the exchange are being accumulated. A negative and falling indicator signals that stocks are being sold. Typically such action confirms the current trend in the index.
Crossovers from positive to negative, or vice versa, may signal the trend has changed in the index or exchange being tracked. When the indicator makes a large move, typically of 100 points or more, from negative to positive territory, that is called a breadth thrust.
It means a large number of stocks moved up after a bearish move. Since the stock market tends to rise over time, this a positive signal and may indicate that a bottom in the index is in and prices are heading higher overall.
When index prices and the indicator are moving in different directions, then the current index trend may lack strength. Bullish divergence occurs when the oscillator is rising while the index is falling. This indicates the index could head higher soon since more stocks are starting to advance.
Bearish divergence is when the index is rising and the indicator is falling. This means fewer stocks are keeping the advance going and prices may start to head lower.
Limitations of Using the McClellan Oscillator
The indicator tends to produce lots of signals. Breadth thrusts, divergence, and crossovers all occur with some frequency, but not all these signals will result in the price/index moving in the expected direction.
The indicator is prone to producing false signals and therefore should be used in conjunction with price action analysis and other technical indicators.
The indicator can also be quite choppy, moving between positive and negative territory rapidly. Such action indicates a choppy market, but this isn't evident until the indicator has made this whipsaw move a few times.
Good luck and a big thanks to Fadior!
GAVAD - Selling after a Strong MovimentThis strategy search for a moment whe the market make two candles are consistently strong, and open a Sell, searching the imediactly correction, on the new candle. It`s easy to see the bars on the histogram graph. Purple Bars represent the candle variation. when on candle cross ove the Signal line the graph plot an Yellow ci, if the second bar crossover the signal a green circle is ploted and the operation start on start of the next candle.
This strategy can be used in a lot of Stocks and other graphs. many times we need a small time of graph, maybe 1 or 5 minutes because the gain shoud be planned to a midle of the second candle. You need look the stocks you will use.
Stocks > 100 dolars isnt great, markets extremly volatly not too. but, Stocks that have a consistently development are very interisting. Look to markets searching maybe 0.5% or 1%.
For this moment, I make the development of a Brasilian Real x American Dollar. In 15 Minutes.
if you use in small timeframe the results can be better.
On this time we make more than 500 trades with a small lot of contracts, without a big percent profitable, but a small profit in each operation, maybe you search more than. To present a real trading system I insert a spreed to present a correct view of the results.
Each stock, Index, or crypto there is a specific configuration?
my suggestion for new stocks
You need choice a stock and using the setup search set over than 70% gain (percent profitable), using a 1% of gain and loss between 1-2%
as the exemple (WDO)
default I prepare a Brazilian Index
6-signal (6% is variation of a candle of the last candle)
10000- multiplicator (its important to configure diferences betwen a stock and an Indice)
gain 3 (this proportion will be set looking you target, how I say, 1% can be good)
loss 8 (this proportion will be set with you bankroll management, how I say, maybe 2%, you need evaluate)
for maximize operations I use in the 1 or 5 minute graph. Timeframes more large make slowlly results,
(but not unable that you use in a 1 hour or a 1 day.)
I make this script by zero. Maybe the code doesnt so organized, but is very easy to understand. If you have any doubts . leave a comment.
I hope help you.
[ChasinAlts]Top-Wicked Good S/R LinesHello Tradeurs, as per usual, I hope everyone is having a FAN-FRIGGIN-TASTIC day. With the soon incoming bull market approaching fast(Nov 7, 2022), there are a few ideas that I've really been trying to push out to help nail a few coins as they are near their bottom peak of this closing Bear Market. This one may seem very similar to the last one I posted but I think this one takes the cake...esp when you see the next script from my 'Market Overview' series that I will be publishing shortly after this one as it is utilizing this new script for a market scanner that will be SUPER legit and profitable. Though it is alway nice to be noticed, I'm glad that I'm relatively unpopular so the few people that are now following me can have some time to make some money with some of these scripts I'm trying to pump out for the benefit of the community. I will rarely give my full analysis of how I take in and utilize these scripts but I can tell you, QUITE A FEW of them are money in the bank. Esp these last few I've done/am doing and even more-so the ones that are soon to come (I'm speaking of about the next 3-4 that I will be attempting to pump out in this next VERY IMPORTANT week.). One more thing I'll add before going to the script is a little alpha(Im pretty certain this is the way it is going but NOTHING is EVERY 100% in life). What I believe should be realized is the bottoming out of MANY of the crypto coins at the VERY bottom of a LONG TERM Cup and Handle (so it seems but shat can still change in the blink of an eye). Thus there are quite a few coins that I believe have already bottomed and wont be returning to said bottom for a few years or so but there are also quite a few still at the brink of the bottomest part before the real market breakout occurs. My goal with these scripts coming out this week to help you all find those coins that have yet to hit their very bottom (thus the ATH/ATL script recently published). Going back in history looking for the lowest points of long term Cup & Handles I will point out 2 key things. Near the center/bottomest part of these historical CnH you will see either Double Bottoms OR a Huge dump and then its V-shaped recovery. After these print the point of no return has occurred where only a few coins will be going lower than these Double Bottoms/V-Shaped recoveries. So the time is at hand. Now that many coins are seemingly pumping after this long consolidation, I believe we need to keep a keen eye out for THE FINAL RUG PULL (as soon as enough degenerates are leveraging Long their entire savings.). What Im saying is be ready for this final rug pull to finally be seeing these Double Bottoms/V-Shaped recoveries VERY soon. DO NOT waste all your capital yet and MAKE SURE to use stop losses or else rather than stop losses you will be burdened with MUCH WORSE losses. Im currently not even in the market bc I am waiting on said rug pull. Ok for the Script now.
This script is similar to the last one but with the previous one, one general set of settings can produce VASTLY different results (might have 2 S/R lines on one coin and 80 on another). I wanted to fix that with this script, turn it into a "Market Overview" Scanner and create alerts for the MO Scanner to be able to get alerted any time a coin is passing its largest wick S/R levels bc DULY NOTE...it is VERY rare that a coin will blow past it if it hasn't approached it recently. That means that a small retrace of 3-5%(or more) is EASY to acquire (with leverage that can really add up with how many coins are in the Kucoin Margin Coin list that I have in my scanners). Now, once price does shoot through a level you best be sure to be looking down the line for a retest of the S/R level it blew past before as they are MANY times the retest level and price will be coming back to it before continuing
in the direction it was going. Depending on the TF your using this could be a few hours to a few days to a few weeks...you get it. With this script you can choose to draw S/R lines 2 ways: 1) by having it plot S/R lines on the end of the largest 2(3,4,5..however many you choose) wicks that the chart has access to. For the scanner ill just be putting the largest 2-3 wicks and set alerts when coming up to them/crossing them & 2) having it draw S/R lines on the ends of the largest X% of wicks. it will be erasing the lines and drawing new ones on each new candle occurrence so the same general settings will no longer be producing VASTLY diff amounts of S/R lines and will be way more consistent amongst the coins for better utilization with the scanner (when I publish it). There is also a Wick Max Cutoff % so for those coins that had it's first few hours printing 100% sized wicks...you can choose to ignore them so they are not taking up one of your top spots for the S/R lines. There is similarly a Wick % min Size that can be selected so if you’re using the top % setting, it will help decrease those coins that can be still plotting 30 lines even though the top 3% of the largest wicks are set in the settings. Hope Im being clear but it's easy enough. I believe in you and your capabilities of comprehending it all and getting it all figured out. So this script is for a visualization for the scanner that I will be uploading soon-after. It's always nice to get a few comments if my ideas/scripts have been helpful to you and please don't hold back if you have something to tell me that I screwed up on (I am still rather new to this coding thing but I like to think I at least have some fresh ideas that aren’t out there in the public library). Talk to you soon and may the force be with your trades. Peace and love people...peace and love. -ChasinAlts out.
CROCEUsing free cash flow instead of ebit, to be able to evaluate stocks that are not yet profitable.
the formulas are
fcf ttm / (not financial operating working capital - Cash + Net Property Plant and Equipment)
and
fcf yield on Enterprice Value
Example CRWD negative ebit, but cash creation, in this case the expenses in research and development go to affect the ebit.
[Sniper] SSL Hybrid + QQE MOD + Waddah Attar StrategyHi. I’m DuDu95.
**********************************************************************************
This is the script for the series called "Sniper".
*** What is "Sniper" Series? ***
"Sniper" series is the project that I’m going to start.
In "Sniper" Series, I’m going to "snipe and shoot" the youtuber’s strategy: to find out whether the youtuber’s video about strategy is "true or false".
Specifically, I’m going to do the things below.
1. Implement "Youtuber’s strategy" into pinescript code.
2. Then I will "backtest" and prove whether "the strategy really works" in the specific ticker (e.g. BTCUSDT) for the specific timeframe (e.g. 5m).
3. Based on the backtest result, I will rate and judge whether the youtube video is "true" or "false", and then rate the validity, reliability, robustness, of the strategy. (like a lie detector)
*** What is the purpose of this series? ***
1. To notify whether the strategy really works for the people who watched the youtube video.
2. To find and build my own scalping / day trading strategy that really works.
**********************************************************************************
*** Strategy Description ***
This strategy is from "SSL QQE MOD 5MIN SCALPING STRATEGY" by youtuber "Daily Investments".
"Daily Investments" claimed that this strategy will make you some money from 100 trades in any ticker in 5 minute timeframe.
### Entry Logic
1. Long Entry Logic
- close > SSL Hybrid Baseline.
- QQE MOD should turn into blue color.
- Waddah Attar Explosion indicator must be green.
2. Short Entry Logic
- close < SSL Hybrid Baseline
- QQE MOD should turn into red color.
- Waddah Attar Explosion indicator must be red.
### Exit Logic
1. Long Exit Logic
- When QQE MOD turn into red color.
2. Short Entry Logic
- When QQE MOD turn into blue color.
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
3. SSL Hybrid Baseline is by default drawn on the chart.
4. If you check EMA filter, EMA would be drawn on the chart.
5. Should add QQE MOD and Waddah Attar Explosion indicator manually if you want to see QQE MOD.
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*** Rating: True or False?
### Rating:
→ 1.5 / 5 (0 = Trash, 1 = Bad, 2 = Not Good, 3 = Good, 4 = Great, 5 = Excellent)
### True or False?
→ False
→ Doesn't Work on 5 minute timeframe. Also, it doesn't work on crypto.
### Better Option?
→ Use this for Day trading or Swing Trading, not for Scalping. (Bigger Timeframe)
→ Although the result was bad at 5 minute timeframe, it was profitable in 1h, 2h, 4h, 8h, 1d timeframe.
→ BTC, ETH was ok.
→ The result was better when I use EMA filter (only on longer timeframe).
### Robust?
→ So So. Although result was bad in short timeframe (e.g. 30m 15m 5m), backtest result was "consistently" profitable on longer timeframe.
→ Also, MDD was not that bad under risk management option on.
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*** Conclusion?
→ Don't use this on short timeframe.
→ Better use on longer timeframe with filter, stoploss and risk management.
ADX W. Wilders(DI+, DI-, DX, ADXR, Equilibrium Point)The reason for publishing the script was the lack of display of important components in the standard ADX indicator, such as DI+, DI-, DX , ADXR, and the absence of a choice of methods for calculating moving averages in the indicator.
According to the book by the author of the ADX indicator, W. Wilder, the indicator components were calculated using the SMA formula, however, the RMA moving average is used in the code of the built-in indicator in TradingView, which shows excellent results, but this is not a classic calculation method. In addition to SMA and RMA, there are also EMA , HMA , WMA , VWMA moving averages to choose from. Added the ability to display lines ADX , ADXR , DX , DI+, DI- and Equilibrium points (when DI+ and DI- are equal or intersect).
ADX Trading Rules
1. Trade the intersections of DI+ and DI-
2. Extreme Point Rule(EPR). EPR is formed when DI+, DI- (Equilibrium point) crosses, forming a trend reversal point at the extremum of the current bar. In the example on the ADX RMA chart, the DI- line is above DI+. Being in a short position at the reverse intersection of the DI- and DI + lines, it is necessary to take the high price of the crossing bar for the reversal point, upon breakdown of which, turn to long. In this example, the breakdown did not take place and the short position remained active, despite the intersection of the DI+ lines over DI-. This rule is an excellent filter that removes unnecessary transactions in the trading system.
3. DI+ > ADX and DI- > ADX. Stop trading trend-following systems.
4. If ADXR > 25, the trading system will be profitable. With ADXR < 20, trend-following systems need to stop trading. Many mistakenly use ADX values instead of ADXR . The author explicitly pointed to ADXR in his book.
5. Equilibrium Point - balance points. The accumulation of these points on the chart means the presence of a flat in the market. Accumulation often appears on a declining ADX after a top has been established on the ADX indicator. The smaller the distance between the points, the less significant movements occurred in the market.
6. For intraday trading of cryptocurrencies use can the following ADX settings:
DI Length = 100
ADX Smoothing = 14
MA Type = VWMA
Flat Zone = 30
P.S. Fragment from an interview with W. Wilder:
OH: You are probably best known for inventing the Relative Strength Index ( RSI ), Average Directional Index ( ADX ) and Average True Range (ATR). Which of these is the most powerful tool for a trader?
WW: The ADX .
OH: Is it the indicator you are most proud of?
WW: I guess so.
Close v Open Moving Averages Strategy (Variable) [divonn1994]This is a simple moving average based strategy that works well with a few different coin pairings. It takes the moving average 'opening' price and plots it, then takes the moving average 'closing' price and plots it, and then decides to enter a 'long' position or exit it based on whether the two lines have crossed each other. The reasoning is that it 'enters' a position when the average closing price is increasing. This could indicate upwards momentum in prices in the future. It then exits the position when the average closing price is decreasing. This could indicate downwards momentum in prices in the future. This is only speculative, though, but sometimes it can be a very good indicator/strategy to predict future action.
What I've found is that there are a lot of coins that respond very well when the appropriate combination of: 1) type of moving average is chosen (EMA, SMA, RMA, WMA or VWMA) & 2) number of previous bars averaged (typically 10 - 250 bars) are chosen.
Depending on the coin.. each combination of MA and Number of Bars averaged can have completely different levels of success.
Example of Usage:
An example would be that the VWMA works well for BTCUSD (BitStamp), but it has different successfulness based on the time frame. For the 12 hour bar timeframe, with the 66 bar average with the VWMA I found the most success. The next best successful combo I've found is for the 1 Day bar timeframe with the 35 bar average with the VWMA.. They both have a moving average that records about a month, but each have a different successfulness. Below are a few pair combos I think are noticeable because of the net profit, but there are also have a lot of potential coins with different combos:
It's interesting to see the strategy tester change as you change the settings. The below pairs are just some of the most interesting examples I've found, but there might be other combos I haven't even tried on different coin pairs..
Some strategy settings:
BTCUSD (BitStamp) 12 Hr Timeframe : 66 bars, VWMA=> 10,387x net profit
BTCUSD (BitStamp) 1 Day Timeframe : 35 bars, VWMA=> 7,805x net profit
BNBUSD (Binance) 12 Hr Timeframe : 27 bars, VWMA => 15,484x net profit
ETHUSD (BitStamp) 16 Hr Timeframe : 60 bars, SMA => 5,498x net profit
XRPUSD (BitStamp) 16 Hr Timeframe : 33 bars, SMA => 10,178x net profit
I only chose these coin/combos because of their insane net profit factors. There are far more coins with lower net profits but more reliable trade histories.
Also, usually when I want to see which of these strategies might work for a coin pairing I will check between the different Moving Average types, for example the EMA or the SMA, then I also check between the moving average lengths (the number of bars calculated) to see which is most profitable over time.
Features:
-You can choose your preferred moving average: SMA, EMA, WMA, RMA & VWMA.
-You can also adjust the previous number of calculated bars for each moving average.
-I made the background color Green when you're currently in a long position and Red when not. I made it so you can see when you'd be actively in a trade or not. The Red and Green background colors can be toggled on/off in order to see other indicators more clearly overlayed in the chart, or if you prefer a cleaner look on your charts.
-I also have a plot of the Open moving average and Close moving average together. The Opening moving average is Purple, the Closing moving average is White. White on top is a sign of a potential upswing and purple on top is a sign of a potential downswing. I've made this also able to be toggled on/off.
Please, comment interesting pairs below that you've found for everyone :) thank you!
I will post more pairs with my favorite settings as well. I'll also be considering the quality of the trades.. for example: net profit, total trades, percent profitable, profit factor, trade window and max drawdown.
*if anyone can figure out how to change the date range, I woul really appreciate the help. It confuses me -_- *
Rob Booker - ADX Breakout updated to pinescript V5Rob Booker - ADX Breakout. The strategy remains unchanged but the code has been updated to pinescript V5. This enables compatibility with all new Tradingview features. Additonally, indicators have been made more easily visible, default cash settings as well as input descriptions have been added.
Rob Booker - ADX Breakout: (Directly taken from the official Tradingview V1 version of the script)
Definition
Rob Booker’s Average Directional Index (ADX) Breakout is a trend strength indicator that affirms the belief that trading in the direction of a trend and continuing to follow its pull is more profitable for traders, while simultaneously reducing risk.
History
ADX was traditionally used and developed to determine a price’s trend strength. It is commonly known as a tool from the arsenal of Rob Booker, experienced entrepreneur and currency trader.
Calculations
Calculations for the ADX Breakout indicator are based on a moving average of price range expansion over a specific period of time. By default, the setting rests at 14 bars, this however is not mandatory, as other periods are routinely used for analysis as well.
Takeaways
The ADX line is used to measure and determine the strength of a trend, and so the direction of this line and its interpretation are crucial in a trader’s analysis. As the ADX line rises, a trend increases in strength and price moves in the trend’s direction. Similarly, if the ADX line is falling, a trend decreases in strength and price then enters a period of consolidation, or retracement.
Traditionally, the ADX is plotted on the chart as a single line that consists of values that range from 0-100. The line is non-directional, meaning that it always measures trend strength regardless of the position of a price’s trend (up or down). Essentially, ADX quantifies trend strength by presenting in both uptrends and downtrends of the line.
What to look for
The values associated with the ADX line help traders determine the most profitable trades and where risk lies in the current trend. It is important to know how to quantify trend strength and distinguish between the varying values in order to understand the differences in trending vs. non-trending conditions. Let’s take a look at ADX values and what they mean for trend strength.
ADX Value:
0-25: Signifies an absent of weak trend
25-50: Signifies a strong trend
50-75: Signifies a very strong trend
75-100: Signifies an extremely strong trend
To delve into this a bit further, let’s assess the meaning of ADX if it is valued below 25. If the ADX line remains below 25 for more than 30 or so bars, price then enters range conditions, making price patterns more distinguishable and visible to traders. Price will move up and down between resistance and support in order to determine selling and buying interest and may then eventually break out into a trend or pattern.
The way in which ADX peaks, ebs, and flows is also a signifier of its overall pattern and trend momentum. The line can clearly indicate to the trader when trend strength is strong versus when it is weak. When ADX peaks are pictured as higher, it points towards an increase in trend momentum. If ADX peaks are pictured as lower - you guessed it - it points towards a decrease in trend momentum. A trend of lower ADX peaks could be a warning for traders to watch prices and manage and assess risk before a trade gets out of hand. Similarly, whenever there is a sudden move that seems out of place or a change in trend character that goes against what you’ve seen before, this should be a clear sign to watch prices and assess risk.
Summary
The ADX Breakout indicator is a trend strength indicator that analyzes price movements relative to trend strength to signal a user when is best for a trade and when is best to manage risk and assess patterns. As long as a trader recognizes strong trends and assesses the risk of each trade properly, they should have no problem using this indicator and utilizing it to work in their favor. In addition, the ADX helps identify trending conditions, but while doing so, also aids traders in finding strong trends to trade. The indicator can even alert traders to specific changes in trend momentum, allowing them to be primed for risk management.
VIDYA Trend StrategyOne of the most common messages I get is people reaching out asking for quantitative strategies that trade cryptocurrency. This has compelled me to write this script and article, to help provide a quantitative/technical perspective on why I believe most strategies people write for crypto fail catastrophically, and how one might build measures within their strategies that help reduce the risk of that happening. For those that don't trade crypto, know that these approaches are applicable to any market.
I will start off by qualifying up that I mainly trade stocks and ETFs, and I believe that if you trade crypto, you should only be playing with money you are okay with losing. Most published crypto strategies I have seen "work" when the market is going up, and fail catastrophically when it is not. There are far more people trying to sell you a strategy than there are people providing 5-10+ year backtest results on their strategies, with slippage and commissions included, showing how they generated alpha and beat buy/hold. I understand that this community has some really talented people that can create some really awesome things, but I am saying that the vast majority of what you find on the internet will not be strategies that create alpha over the long term.
So, why do so many of these strategies fail?
There is an assumption many people make that cryptocurrency will act just like stocks and ETFs, and it does not. ETF returns have more of a Gaussian probability distribution. Because of this, ETFs have a short term mean reverting behavior that can be capitalized on consistently. Many technical indicators are built to take advantage of this on the equities market. Many people apply them to crypto. Many of those people are drawn down 60-70% right now while there are mean reversion strategies up YTD on equities, even though the equities market is down. Crypto has many more "tail events" that occur 3-4+ standard deviations from the mean.
There is a correlation in many equities and ETF markets for how long an asset continues to do well when it is currently doing well. This is known as momentum, and that correlation and time-horizon is different for different assets. Many technical indicators are built based on this behavior, and then people apply them to cryptocurrency with little risk management assuming they behave the same and and on the same time horizon, without pulling in the statistics to verify if that is actually the case. They do not.
People do not take into account the brokerage commissions and slippage. Brokerage commissions are particularly high with cryptocurrency. The irony here isn't lost to me. When you factor in trading costs, it blows up most short-term trading strategies that might otherwise look profitable.
There is an assumption that it will "always come back" and that you "HODL" through the crash and "buy more." This is why Three Arrows Capital, a $10 billion dollar crypto hedge fund is now in bankruptcy, and no one can find the owners. This is also why many that trade crypto are drawn down 60-70% right now. There are bad risk practices in place, like thinking the martingale gambling strategy is the same as dollar cost averaging while also using those terms interchangeably. They are not the same. The 1st will blow up your trade account, and the 2nd will reduce timing risk. Many people are systematically blowing up their trade accounts/strategies by using martingale and calling it dollar cost averaging. The more risk you are exposing yourself too, the more important your risk management strategy is.
There is an odd assumption some have that you can buy anything and win with technical/quantitative analysis. Technical analysis does not tell you what you should buy, it just tells you when. If you are running a strategy that is going long on an asset that lost 80% of its value in the last year, then your strategy is probably down. That same strategy might be up on a different asset. One might consider a different methodology on choosing assets to trade.
Lastly, most strategies are over-fit, or curve-fit. The more complicated and more parameters/settings you have in your model, the more likely it is just fit to historical data and will not perform similar in live trading. This is one of the reasons why I like simple models with few parameters. They are less likely to be over-fit to historical data. If the strategy only works with 1 set of parameters, and there isn't a range of parameters around it that create alpha, then your strategy is over-fit and is probably not suitable for live trading.
So, what can I do about all of this!?
I created the VIDYA Trend Strategy to provide an example of how one might create a basic model with a basic risk management strategy that might generate long term alpha on a volatile asset, like cryptocurrency. This is one (of many) risk management strategies that can reduce the volatility of your returns when trading any asset. I chose the Variable Index Dynamic Average (VIDYA) for this example because it's calculation filters out some market noise by taking into account the volatility of the underlying asset. I chose a trend following strategy because regressions are capturing behaviors that are not just specific to the equities market.
The more volatile an asset, the more you have to back-off the short term price movement to effectively trend-follow it. Otherwise, you are constantly buying into short term trends that don't represent the trend of the asset, then they reverse and loose money. This is why I am applying a trend following strategy to a 4 hour chart and not a 4 minute chart. It is also important to note that following these long term trends on a volatile asset exposes you to additional risk. So, how might one mitigate some of that risk?
One of the ways of reducing timing risk is scaling into a trade. This is different from "doubling down" or "trippling down." It is really a basic application of dollar cost averaging to reduce timing risk, although DCA would typically happen over a longer time period. If it is really a trend you are following, it will probably still be a trend tomorrow. Trend following strategies have lower win rates because the beginning of a trend often reverses. The more volatile the asset, the more likely that is to happen. However, we can reduce risk of buying into a reversal by slowly scaling into the trend with a small % of equity per trade.
Our example "VIDYA Trend Strategy" executes this by looking at a medium-term, volatility adjusted trend on a 4 hour chart. The script scales into it with 4% of the account equity every 4-hours that the trend is still up. This means you become fully invested after 25 trades/bars. It also means that early in the trade, when you might be more likely to experience a reversal, most of your account equity is not invested and those losses are much smaller. The script sells 100% of the position when it detects a trend reversal. The slower you scale into a trade, the less volatile your equity curve will be. This model also includes slippage and commissions that you can adjust under the "settings" menu.
This fundamental concept of reducing timing risk by scaling into a trade can be applied to any market.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
2x take profit, move stop loss to entryTwo take profit targets moving stop loss to entry after first take profit hit
This strategy shows a method to achieve the following trade management:
1) Open a position with two take profit targets
2) When first take profit is hit, move the stop loss to entry price
3) Position is closed when either second take profit is hit or position is stopped out at entry
Trading Conditions
The trading conditions used in this script are for illustrative purposes only and are not meant to be profitable.
Bollinger Bands
Used to show areas where price is moving outside of the normal range
Stochastic
Used to show overbought and oversold conditions.
Green dots are plotted when the K line crosses over its SMA. Red dots are plotted when the K line crosses under its SMA.
The option to use overbought/oversold thresholds is again illustrative.
