Bollinger Bands BAT/USDT 30minThis is ready to use Bollinger Band strategy that was backtested on the data from the previous year 2019.
The main purpose of this strategy is to determine trades with the highest probability of success, to keep a consistent portfolio growth throughout the year. This strategy cherry-picks the most reliable points of entry on a particular timeframe (30m) for the particular asset (BAT/USDT). The backtest shows a great result of 78.95% profitability with the maximum drawdown of -4.02%. This is one of my strategies out of the group of automated strategies that helps to grow my portfolio steadily.
You are welcome to change inputs and backtest the following strategy. Any comments or ideas would be appreciated.
If you are happy with existing results and would like to automate the strategy, which can be done through alerts, then you need to convert it to study and add alerts in the code.
Let me know if you are interested in that and I will create a study based on this strategy.
Pesquisar nos scripts por "the strat"
Strategy VS Buy & HoldSUMMARY:
A strategy wrapper that makes a detailed and visual comparison between a given strategy and the buy & hold returns of the traded security.
DESCRIPTION:
TradingView has a "Buy & Hold Return" metric in the strategy tester that is often enough to assess how our strategy compares to a simple buy hold. However, one may want more information on how and when your strategy beats or is beaten by a simple buy & hold strategy. This script aims to show such detail by providing a more comprehensive metrics and charting the profit/loss of the given strategy against buy & hold.
As seen in the script, it plots/draws 4 elements:
1) Strategy P/L: strategy net profit + strategy open profit
2) Buy & Hold P/L: unrealized return
3) Difference: Strategy P/L - Buy & Hold P/L
4) Strategy vs Buy Hold Stats
> Percent of bars strategy P/L is above Buy & Hold
> Percent of bars strategy P/L is below Buy & Hold
> All Time Average Difference
ADJUSTABLE PARAMETERS:
All labels/panels can be disabled by unchecking these two options:
>bnh_info_panel = input(true, title='Enable Info Panel')
>bnh_indicator_panel = input(true, title='Enable Indicator Panel')
Comparison Date Range can be changed to better isolate specific areas:
>From Year, From Month, From Day
default: 1970 01 01
>To Year, To Month, To Day
default: 2050 12 31
Default settings basically covers all historical data.
HOW TO USE:
The default script contains a simple 50-200 SMA cross strategy, just delete and replace it. Those are everything between these lines:
/////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////STRATEGY SCRIPT START//////////////////////////////////
(STRATEGY SCRIPT GOES HERE)
//////////////////////////////STRATEGY SCRIPT END////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////
Removing all plots and drawings from your strategy is advisable.
If you are going to use the Comparison Date Range, apply "bnh_timeCond" to your strategy to align the dates. A sample on how it’s applied can be seen on the Placeholder MA cross strategy.
Note: bnh_timeCond returns a boolean series
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.
Total Trend Follow Strategy with Pyramid and DCA
Introduction
This is a Pine 4 trend following 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 trend following strategy, the behavior of the script is to buy on strength and sell on weakness. As such the trade orders maintain its directional bias according to price pressure. What you will see on the chart is long positions on the left side of the mountain and short on the right. Long and short positions are not intermingled as long as there exists a detectable trend. This is extremely beneficial feature in long running bull or bear markets. The script uses multiple setups to avoid the situation where you got in on the trend, took a small profit but couldn’t get back in because the logic is waiting for a pullback or some other intricate condition.
Deep draw-downs are a characteristic of trend following systems and this system is no different. However, this script makes use of the TradingView pyramid feature accessible from the properties tab. Additional trades can be placed in the draw-down space increasing the position size and thereby increasing the profit or loss when the position finally closes. Each individual add on trade increases its order size as a multiple of its pyramid level. This makes it easy to comply with NFA FIFO Rule 2-43(b) if the trades are executed here in America. The inputs dialog box contains various settings to adjust where the add on trades show up, under what circumstances and how frequent if at all. Please be advised that pyramiding is an advanced feature and can wipe out your account capital if your not careful. During the backtest use modest setting with realistic capital until you discover what you think you can handle.
In addition to pyramiding this script employs DCA which enables users to experiment with loss recovery techniques. This is another advanced feature which can increase the order size on new trades in response to stopped out or winning streak trades. The script keeps track of debt incurred from losing trades. When the debt is recovered the order size returns to the base amount specified in the TV properties tab. The inputs for this feature include a limiter to prevent your account from depleting capital during runaway markets. The main difference between DCA and pyramids is that this implementation of DCA applies to new trades while pyramids affect open positions. DCA is a popular feature in crypto trading but can leave you with large “bags” if your not careful. In other markets, especially margin trading, you’ll need a well funded account and much experience.
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 nine indicators on two time frames. The chart (primary) interval and one higher time frame which is based on the primary. The higher time frame identifies the trend for which the primary will trade. I’ve tried to keep the higher time frame around five times greater than the primary. 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 alligator itself is used to identify the trend main body.
The entire script is around 1700 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 over a year 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. Though it can be configured to work on any interval between 5 minutes and 1 day, trend trading is generally a longer term paradigm. For day trading the 10 to 15 minute interval will allow you to catch momentum breakouts. For intraweek trades 30 minutes to 1 hour should give you a trade every other a day. Four hours and above are for seasoned deep pocket traders. 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. Since this trading system is featured as two separate scripts, indicator repainting is addressed in the study version. The strategy (this script) is intended to be used on historical data to determine the appropriate trading inputs to apply in the study. As such, the higher time frame of this strategy will indeed repaint. Please do not attempt to trade from the strategy. Please see the study version for more information.
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. However, alerts that are subsequently fired off when triggered in the study are dispatched from the TradingView servers one bar later from the study plot. Therefore the alert you actually receive on your cell phone matches the strategy plot but is one bar later than the study plot. A lot can happen in four hours if you are trading off a 240 bar.
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 seven 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 pyramids, 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 3. 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 3.
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 blue markers and short trades on the red.
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. Blue is long and red is short.
Step 8. Try a different indicator from section 3 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. Turn off Show Markers in Section 3.
Step 10. Enable the Symmetrical and Deviation calculation models at the top of section 5 and 6 (Symmetrical, Deviation).
Step 11. Put in your Minimum Profit and Stop Loss in the first section. This is in pips or currency basis points (chart right side scale)
Step 12. Return to step 3 and select a Trading Mode (Long, Short, BiDir, Flip Flop). If you are planning to trade bidirectionally its best to configure long first then short. Combine them with BiDir or Flip Flop after setting up both sides of the trade individually.
Step 13. Trades should be showing on the chart.
Step 14. Make adjustments to the Vertex fields in section 3 until the TradingView performance report is showing a profit.
Step 15. Change indicators and repeat step 14. Pick the best indicator.
Step 16. Use the check boxes in sections 5 and 6 to improve the performance of each side.
Step 17. Try adding the Correlation calculation model to either side. This model can sometimes produce a negative result but can be improved by enabling “Adhere To Markers” or “Narrow Correlation Scope” in the sections 5 and 6.
Step 18. Enable the reporting conditions in section 7. 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 19. Examine the chart and see that trades are being placed in accordance with your desired trading model.
Step 20. 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.
Combo Backtest 123 Reversal & Bill Williams Averages. 3Lines This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator calculates 3 Moving Averages for default values of
13, 8 and 5 days, with displacement 8, 5 and 3 days: Median Price (High+Low/2).
The most popular method of interpreting a moving average is to compare
the relationship between a moving average of the security's price with
the security's price itself (or between several moving averages).
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & Bear Power This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
Bear Power Indicator
To get more information please see "Bull And Bear Balance Indicator"
by Vadim Gimelfarb.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & (H-L)/C Histogram This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This histogram displays (high-low)/close
Can be applied to any time frame.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & Bandpass FilterThis is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The related article is copyrighted material from
Stocks & Commodities Mar 2010
You can use in the xPrice any series: Open, High, Low, Close, HL2, HLC3, OHLC4 and ect...
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & Average True Range Trailing Stops This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
Average True Range Trailing Stops Strategy, by Sylvain Vervoort
The related article is copyrighted material from Stocks & Commodities Jun 2009
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal and ADXR This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
The Average Directional Movement Index Rating (ADXR) measures the strength
of the Average Directional Movement Index (ADX). It's calculated by taking
the average of the current ADX and the ADX from one time period before
(time periods can vary, but the most typical period used is 14 days).
Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening
and weakening trends. However, because it represents an average of ADX, values
don't fluctuate as dramatically and some analysts believe the indicator helps
better display trends in volatile markets.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal and Accelerator Oscillator (AC) This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The Accelerator Oscillator has been developed by Bill Williams
as the development of the Awesome Oscillator. It represents the
difference between the Awesome Oscillator and the 5-period moving
average, and as such it shows the speed of change of the Awesome
Oscillator, which can be useful to find trend reversals before the
Awesome Oscillator does.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal and Absolute Price Oscillator (APO) This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
The Absolute Price Oscillator displays the difference between two exponential
moving averages of a security's price and is expressed as an absolute value.
How this indicator works
APO crossing above zero is considered bullish, while crossing below zero is bearish.
A positive indicator value indicates an upward movement, while negative readings
signal a downward trend.
Divergences form when a new high or low in price is not confirmed by the Absolute Price
Oscillator (APO). A bullish divergence forms when price make a lower low, but the APO
forms a higher low. This indicates less downward momentum that could foreshadow a bullish
reversal. A bearish divergence forms when price makes a higher high, but the APO forms a
lower high. This shows less upward momentum that could foreshadow a bearish reversal.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Strategies 123 Reversal and 3-Bar-Reversal-Pattern This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
This startegy based on 3-day pattern reversal described in "Are Three-Bar
Patterns Reliable For Stocks" article by Thomas Bulkowski, presented in
January,2000 issue of Stocks&Commodities magazine.
That pattern conforms to the following rules:
- It uses daily prices, not intraday or weekly prices;
- The middle day of the three-day pattern has the lowest low of the three days, with no ties allowed;
- The last day must have a close above the prior day's high, with no ties allowed;
- Each day must have a nonzero trading range.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal and 2/20 EMA This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Please, use it only for learning or paper trading. Do not for real trading.
WARNING:
- For purpose educate only
- This script to change bars colors.
XPloRR MA-Buy ATR-Trailing-Stop Long Term Strategy Beating B&HXPloRR MA-Buy ATR-MA-Trailing-Stop Strategy
Long term MA Trailing Stop strategy to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the EMA(blue) crossing over the SMA curve(orange).
My sell strategy is triggered by another EMA(lime) of the close value crossing the trailing stop(green) value.
The trailing stop value(green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between high and low values.
Every stock has it's own "DNA", so first thing to do is find the right parameters to get the best strategy values voor EMA, SMA and Trailing Stop.
Then keep using these parameter for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Here are the parameters:
Exponential MA: buy trigger when crossing over the SMA value (use values between 11-50)
Simple MA: buy trigger when EMA crosses over the SMA value (use values between 20 and 200)
Stop EMA: sell trigger when Stop EMA of close value crosses under the trailing stop value (use values between 8 and 16)
Trailing Stop #ATR: defines the trailing stop value as a multiple of the ATR(15) value
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now):
BAR(Barco): EMA=11, SMA=82, StopEMA=12, Stop#ATR=9
Buy&HoldProfit: 45.82%, NetProfit: 294.7%, #Trades:8, %Profit:62.5%, ProfitFactor: 12.539
AAPL(Apple): EMA=12, SMA=45, StopEMA=12, Stop#ATR=6
Buy&HoldProfit: 2925.86%, NetProfit: 4035.92%, #Trades:10, %Profit:60%, ProfitFactor: 6.36
BEKB(Bekaert): EMA=12, SMA=42, StopEMA=12, Stop#ATR=7
Buy&HoldProfit: 81.11%, NetProfit: 521.37%, #Trades:10, %Profit:60%, ProfitFactor: 2.617
SOLB(Solvay): EMA=12, SMA=63, StopEMA=11, Stop#ATR=8
Buy&HoldProfit: 43.61%, NetProfit: 151.4%, #Trades:8, %Profit:75%, ProfitFactor: 3.794
PHIA(Philips): EMA=11, SMA=80, StopEMA=8, Stop#ATR=10
Buy&HoldProfit: 56.79%, NetProfit: 198.46%, #Trades:6, %Profit:83.33%, ProfitFactor: 23.07
I am very curious to see the parameters for your stocks and please make suggestions to improve this strategy.
Long Bollinger Bands StrategyLong Bollinger Bands Strategy (XAUUSD) — Lower Band Reversal + 4-Step Scaling + Daily DD Guard
Long Bollinger Bands Strategy is a long-only Bollinger Bands reversal/mean-reversion strategy designed mainly for XAUUSD. It looks for a bearish push below the Lower Band followed by a bullish reclaim on candle close, then optionally scales in up to 4 entries (E1–E4) as price pulls back.
1) Risk Management & Position Sizing
The strategy includes a USD-based risk input: Risk per setup (USD).
It automatically calculates position size using the average SL distance across the 4-entry structure, then distributes size across entries with built-in weighting.
BackTest Lot checkbox:
OFF (default): uses normalized sizing (qty divided by 100)
ON: uses raw qty for backtesting workflows
2) SL/TP Management (Locked SL + Optional Range TP)
Stop Loss (SL): based on SL distance (pips from entry) from E1.
Take Profit (TP):
If TP (pips) > 0: fixed pip TP from E1
If TP (pips) = 0: TP is based on the signal candle range (high–low)
SL Lock: once the stop is tightened, it never loosens again (only moves in a protective direction) until the trade closes.
3) Daily Drawdown Protection
Tracks equity by day and stops opening new positions once Max daily drawdown (USD) is reached for that day.
4) Notes / Disclaimer
This strategy does not use volume, RSI, fundamentals, news filters, or session filters. Users should apply discretion and consider confirmations from other tools and market context. Results depend on symbol settings, spread, commission, and volatility regime. Always forward-test before using in live trading.
Designed for XAUUSD. The script uses an internal pip conversion (pipSize = 0.1) consistent with common gold quoting; verify your broker’s pip definition for best alignment.
5) Suggested Usage
Best used during volatile conditions or after a clear lower-band sweep and reclaim.
Consider pairing with trend filters or higher-timeframe bias.
6) Release Notes
Initial release: Long-only BB reclaim logic with 4-step scaling
Added: SL/TP lock logic and visual SL/TP lines
Added: Daily drawdown guard and backtest lot toggle OANDA:XAUUSD
StrategyScript77 Is a rule-based strategy built on top of an Ichimoku based engine.
Ichimoku concepts are used as the backbone for trend and momentum filtering, so the strategy tends to stay on the side of the dominant move instead of fighting it.
The name “Super77” comes from the behavior I consistently observed in testing because the win rate tends to hover around the 70–80% range, often clustering around ~77% when used as intended.
It’s not a promise or guarantee, but it reflects the core design philosophy: frequent, relatively small but steady wins, with controlled and manageable losses.
Trading Style – Built for Conservative Traders
Super77 is intentionally designed for traders who prefer a conservative and calm approach:
Entries only at bar close
The strategy waits for bar close confirmation before entering a position. No intrabar guessing, no chasing half-formed signals. If the signal is still valid at close, only then will it enter.
Exits automated on bar close
Exits are also managed on bar close, which makes the logic transparent, easy to review on the chart, and more robust in backtesting compared to tick-based or intrabar hacks.
Semi-auto friendly
If you like to keep some discretion, you can treat it as semi-automatic:
Let the strategy generate entry signals
Manually cancel or skip certain trades if market context changes (news, extreme volatility, etc.)
This combination makes Super77 suitable for traders who don’t want to stare at the screen all day but still want structure and automation.
How to Use
Works best with bar-close execution (avoid trying to simulate intrabar fills if you want consistent behavior).
Designed for conservative, trend-aligned trading, not for hyper-scalping or news gambling.
Can be used as:
Fully automated (let all entries/exits trigger on bar close), or
Semi-automated (use alerts/signals but manually cancel some entries).
Step-by-Step: Automation with Cornix (Webhook Setup)
You can automate Super77 using Cornix by connecting TradingView alerts to your Cornix group via webhook.
Note: Exact button names may differ slightly depending on Cornix / TradingView updates, but the flow is always the same:
Cornix group → get webhook URL & mapping → TradingView alerts → signals sent to Cornix.
(Optional) Map specific pairs / directions
If you use UUID / signal mapping per symbol and per side (long/short), set them up in Cornix according to your own template.
Super77 can be used either:
On a single pair (simple setup), or
On multiple pairs if your alert / webhook structure supports that. So you can pick many pairs with 1 script.
Final Notes & Disclaimer
Super77 is an educational and experimental trading tool, not financial advice.
Past performance in back tests does not guarantee future results.
Always:
Test on demo or paper first
Adjust risk to match your own profile
Accept that losses and drawdowns are a natural part of any strategy
If you’re looking for a strategy that reflects a conservative, confirmation-based trading style with a focus on steady win rate and smoother equity behavior, Super77 was built exactly with that mindset in mind.
GIX Analizor strategiiGIX Analyzer – Intelligent Time Filters + X Strategy
This script combines the X Strategy with an advanced system for filtering trades based on time intervals. The strategy allows:
Filtering by preset trading hours (active sessions )
Filtering by a fully customizable time interval (hour + minute, Romania time )
Filtering by calendar range (Start Date → End Date)
Simultaneous activation of both time-filter modes for maximum control
Trading only within valid time ranges, while keeping all logic unchanged
This indicator provides high flexibility for testing and optimizing trading entries based on hours, minutes, and calendar periods—while preserving the simplicity and efficiency of any strategy
2 Dip/Tepe + Destek/Direnç + Tek Sinyal Stratejisi⭐ A Brief Summary of What the Strategy Does
🎯 1) Market analysis is being released (bottom-top analysis)
It automatically finds pivot bottoms and pivot tops on the strategic chart. Then:
If the bottoms are rising (HL – High Low): the trend is upward
If the tops are falling (LH – Lower High): the trend is downward
it interprets this.
🎯 2) Support and resistance lines are formed
Last pivot top = resistance line
Last pivot bottom = support line
These lines are automatically drawn on the chart.
🎯 3) Breakout is expected according to the trend structure
For LONG:
The last two bottoms will be rising bottoms
The price will rise above the last resistance line
This gives a single LONG signal.
For SHORT:
The last two peaks will be falling peaks
The price will fall below the support line
This gives a single SHORT signal.
YCGH Ultimate Stocks Breakout Sniper📈 YCGH Ultimate Stocks Breakout Sniper
Overview
A sophisticated momentum-based breakout strategy designed to capture high-probability directional moves during volatility expansion phases. This system identifies breakout opportunities when price decisively breaks through established ranges, combining multiple technical filters to enhance signal quality and minimize false breakouts.
🎯 Strategy Features
Core Methodology:
Proprietary breakout detection algorithm
Multi-layered confirmation filters for signal validation
Adaptive trailing stops for profit protection
Systematic risk management with daily drawdown controls
Key Components:
✅ Volatility Expansion Filter - Only trades during periods of elevated market volatility to avoid choppy, range-bound conditions
✅ Optional Trend Alignment - Configurable trend filter (EMA/SMA/RMA/WMA) to align entries with broader market direction
✅ ROC Momentum Filter - Daily rate-of-change filter to capture strong momentum days (optional)
✅ Comprehensive Exit Strategy:
Fixed stop-loss (default 2%)
Take-profit targets (default 9%)
Dynamic trailing stops (2% activation, 0.5% offset)
✅ Flexible Direction Trading:
Auto-detect mode: Long+Short for perpetuals, Long-only for spot/equities
Manual override options available
Suitable for both crypto and stock markets
📊 Market Applicability
Optimized for: Cryptocurrency perpetual contracts and equity markets (1H-4H timeframes)
Also effective on: Futures and high-liquidity spot markets
The strategy adapts to different market regimes through configurable volatility and trend filters, making it versatile across various trading instruments and timeframes.
⚙️ Risk Management
Position Sizing: Percentage-based allocation with leverage support
Intraday Loss Limit: Maximum 10% drawdown protection (configurable)
Realistic Cost Modeling: 0.025% commission + 1 tick slippage
No Pyramiding: Single position management for controlled risk exposure
📈 Performance Visualization
Includes a comprehensive monthly returns table displaying:
Year-by-year performance breakdown
Monthly profit/loss percentages
Visual color-coding (green for profits, red for losses)
Clean, modern design with transparent styling
🔐 Access & Pricing
This is a PROTECTED, invite-only strategy.
The source code is not open-source and requires paid access for usage.
How to Get Access:
📧 Email: brijamohanjha@gmail.com
Include in your email:
Your TradingView username
Markets/assets you plan to trade
Preferred timeframe
What You'll Receive:
Full strategy access with invite-only permissions
Complete parameter documentation
Setup and optimization guidance
Implementation support
⚠️ Important Disclosures
Backtesting Parameters:
Commission: 0.025% per trade
Slippage: 1 tick
Results reflect realistic trading conditions
Risk Warning:
Past performance does not guarantee future results. This strategy involves substantial risk and may not be suitable for all investors. Users should thoroughly understand the risks and customize parameters based on their risk tolerance and market conditions.
📞 Contact for Access
Email: brijamohanjha@gmail.com
For questions about functionality, pricing, optimization, or market-specific settings, please reach out via email.
Note: This is a premium, paid strategy. Access is granted manually after consultation and payment confirmation.
Pro Bollinger Bands Strategy [Breno]This strategy excels in highly volatile financial instruments, including cryptocurrencies, high-beta stocks, commodity futures, and certain exchange-traded funds (ETFs) that exhibit clear mean-reversion characteristics around their Bollinger Bands. The system's ability to utilize scaling (position averaging) and an ATR-based stop loss makes it particularly effective in markets with significant price swings, allowing the trader to capture profits from price extremes while managing increased volatility-related risk.
Core Strategy Logic
This Strategy implements a comprehensive trend-following and mean-reversion strategy primarily leveraging the Bollinger Bands (BB) indicator for entry and exit signals, complemented by an Average True Range (ATR)-based Stop Loss mechanism and an optional EMA filter. It is designed with robust features for capital management, including configurable leverage and a sophisticated position averaging (scaling) system.
Long Entry: A long position is initiated when the closing price crosses over the Lower Bollinger Band (ta.crossover(close,lowerBB)). This signals a potential mean-reversion opportunity following a price dip.
Short Entry: A short position is initiated when the closing price crosses under the Upper Bollinger Band (ta.crossunder(close,upperBB)). (Note: Short entries are disabled by default in the script inputs).
Exit Conditions (Profit Target): Long positions aim to exit upon interaction with the Upper Bollinger Band. Users can select from three exit methods:
"Close When Touch": Exits when close≥upperBB.
"Close Above then Below": Exits when the previous close was above the upper band, and the current close is below it (a reversal signal).
"High Above": Exits when high>upperBB. The strategy features an optional profitOnly setting, which restricts all exits to only occur if the trade is currently in profit (i.e., close is above the strategy.position_avg_price for longs).
Key Features and Customization
Bollinger Bands & Filters -
Customizable BB Parameters: The Length and Deviation of the Bollinger Bands are fully adjustable, allowing users to fine-tune the sensitivity of the entry and exit signals.
Optional EMA Filter: An optional EMA Filter can be enabled to align entries with the prevailing trend, where a Long entry is only permitted if close≥EMA(EmaFilterRange).
Risk and Capital Management -
Equity Allocation: Position size is dynamically calculated based on a Percentage of Equity (capitalPerc) combined with the set Leverage multiplier.
Dynamic Stop Loss (ATR-Based):
An optional Stop Loss (SL) is calculated using a multiple (slAtrInput) of the Average True Range (ATR).
The SL is set relative to the entry price upon trade activation, providing a volatility-adjusted risk management layer.
Position Averaging (Scaling): The script supports the addition of multiple units (pyramiding) to an existing position based on three user-selected criteria:
"No": No averaging.
"Percent": Adds to the position if the price has dropped by a set percentage (addPct) from the average price.
"ATR": Adds to the position if the current price is significantly below a calculated ATR-based support level from the average price.
Volume Momentum Strategy [MA/VWAP Cross]Deconstructing the Volume Momentum Strategy: An Analysis of MA-VWAP Cross Mechanics
Introduction
The "Volume Momentum Strategy " is a technical trading algorithm programmed in Pine Script v6 for the TradingView platform. At its core, the strategy is a trend-following system that utilizes the interaction between a specific Moving Average (MA) and the Volume Weighted Average Price (VWAP) to generate trade signals. While the primary execution logic relies on price crossovers, the strategy incorporates a sophisticated secondary layer of analysis using the Commodity Channel Index (CCI) and Stochastic Oscillator. Uniquely, these secondary indicators are applied to volume data rather than price, serving as a gauge for market participation and momentum intensity.
The Core Engine: MA and VWAP Crossover
The primary engine driving the strategy's buy and sell decisions is the crossover relationship between a user-defined Moving Average and the VWAP.
1. The Anchor (VWAP): The strategy calculates the Volume Weighted Average Price based on the HLC3 (High, Low, Close divided by 3) source. VWAP serves as the dynamic benchmark for "fair value" throughout the trading session.
2. The Trigger (Moving Average): The script allows for flexibility in defining the "fast" line, offering options such as Simple (SMA), Exponential (EMA), or Hull Moving Averages.
3. The Signal:
o A Long (Buy) signal is generated when the chosen MA crosses over the VWAP. This suggests that short-term price momentum is exceeding the average volume-weighted price of the session, indicating bullish sentiment.
o A Short (Sell) signal is generated when the MA crosses under the VWAP, indicating bearish pressure where price is being pushed below the session's volume-weighted average.
The Role of CCI and Stochastic: Analyzing Volume Momentum
The prompt specifically inquires about how the CCI and Stochastic indicators fit into this process. In standard technical analysis, these oscillators are used to identify overbought or oversold price conditions. However, this strategy repurposes them to analyze Volume Momentum.
1. The Calculation
Instead of using close prices as the input source, the script passes volume data into both indicator functions:
• Volume CCI: Calculated as ta.cci(volume, cciLength). This measures the deviation of current volume from its statistical average.
• Volume Stochastic: Calculated as ta.stoch(volume, volume, volume, stochLength). This gauges the current volume relative to its recent range.
2. The "Volume Spike" Condition
The strategy combines these two indicators to define a specific market condition labeled isVolumeSpike. A volume spike is confirmed only when both conditions are met simultaneously:
• The Volume CCI must be greater than a defined threshold (default: 100).
• The Volume Stochastic must be greater than a defined threshold (default: 80).
3. Integration into the Process
It is critical to note how this script currently applies this "Volume Spike" logic:
• Visual Confirmation: In the current version of the code, the isVolumeSpike boolean is used strictly for visual feedback. When a spike is detected, the script paints the specific price bar yellow and plots a small triangle marker below the bar.
• Strategic Implication: While the code calculates these metrics, the variables long_condition and short_condition currently rely solely on the MA/VWAP crossover. The developer has left the volume logic as a visual overlay, noting in the comments that it serves as a "visual/alert" or a potential filter.
• Potential Alpha: Conceptually, this setup implies that a trader should look for the MA/VWAP crossover to occur coincidentally with—or shortly after—a "Volume Spike" (yellow bar). This would confirm that the price move is backed by significant institutional participation (volume) rather than just retail noise.
Risk Management and Time Constraints
The strategy wraps these technical signals in a robust risk management framework. It includes hard-coded time windows (start/stop trading times) and a "Close All" function to prevent holding positions overnight. Furthermore, it employs both percentage-based and dollar-based Stop Loss and Take Profit mechanisms, ensuring that every entry—whether generated by a high-momentum crossover or a standard trend move—has a predefined exit plan.
Conclusion
The "Volume Momentum Strategy" is a hybrid system. It executes trades based on the reliable trend signal of MA crossing VWAP but informs the trader with advanced volume analytics. By processing volume through the CCI and Stochastic calculations, it provides a "heads-up" display regarding the intensity of market participation, allowing the trader to distinguish between low-volume drifts and high-volume breakout moves.
TrendSight📌 TrendSight — The All-in-One Multi-Timeframe Trend Engine
Key Features & Logic
Multi-Timeframe Trend Confirmation:
Entries are filtered by confirming bullish/bearish alignment across three distinct Supertrend timeframes (e.g., 5-min, 15-min, 45-min, etc.), combined with an EMA and volatility filter, to ensure high-conviction trades that's a powerful combination! Designing the entire strategy around the 15-minute timeframe (M15) and focusing on high-volatility coins maximizes the strategy's effectiveness .
Guaranteed Single-Entry per Signal:
The strategy uses a powerful manual flag and counter system to ensure trades fire only once when a new signal begins. It absolutely prevents immediate re-entry if the signal remains true, waiting instead for the entire trend condition to reset to false.
Dynamic Trailing Stop Loss:
The Stop Loss is set to a moving Supertrend line (current_supertrend), ensuring tight risk management that trails the price as the trade moves into profit.Guaranteed Take Profit (4% Run-up): Uses a precise Limit Order via strategy.exit() to capture profits instantly at a 4% run-up. This ensures accurate profit capture, even on sudden spikes (wicks).
Automated Risk Management:
Position size is dynamically calculated based on a fixed risk percentage (default 2% of equity) relative to the distance to the trailing stop.
🔥 Core Components
1. Adaptive Multi-Timeframe SuperTrend Dashboard
The backbone of mTrendSight is a fully customizable SuperTrend system, enhanced with a multi-timeframe confirmation table displaying ST direction & value.
This compact “Trend Dashboard” provides instant clarity on higher-timeframe direction, trend strength, and market bias.
2. Dynamic Support & Resistance Channels
Automatically detects the strongest support/resistance zones using pivot clustering.
Key Features:
Clustered S/R Channels instead of thin lines
Adaptive width based on recent swings
Breakout markers (optional) for continuation signals
Helps identify structural zones, retest areas, and liquidity pockets
3. Multi-Timeframe Color-Coded EMAs
Plot up to three EMAs, each optionally pulled from a higher timeframe.
Benefits:
Instant visual trend alignment
Bullish/Bearish dynamic color shifts
Precision EMA value table for trade planning
Works perfectly with ST & RSI for multi-layer confirmation
4. Linear Regression Trend Channel
A statistically driven trend channel that measures the most probable path of price action.
Highlights:
Uses Pearson’s R to determine trend reliability
Provides a Confidence Level to judge whether trend slope is credible
Ideal for determining over-extension and mean-reversion zones
5. ATR Volatility Analyzer
A lightweight but powerful volatility classifier using ATR.
Features:
Detects High, Low, or Normal volatility
Clean table display
Helps filter entries during low-energy markets
Strengthens trend-following filters when volatility expands
6. RSI Momentum & Trend Classifier
A significantly improved RSI with multi-layer smoothing and structure-based classification.
Provides:
Bullish / Bearish / Neutral momentum states
Short-term momentum vs long-term RSI trend
Perfect for early trend shifts, pullback entries, and momentum confirmation
⚙️ How the Strategy Works (Execution Logic)
📌 Multi-Timeframe Supertrend + EMA + Volatility Confirmation
Entries are only triggered when:
Multiple Supertrend timeframes align (e.g., 5m + 15m + 45m)
EMA direction aligns with the trend
Volatility conditions (ATR filter) is not Low allow high-probability moves
This ensures strong directional confluence before every trade.
📌 Guaranteed Single-Entry Logic
The strategy uses a flag + counter system to ensure:
Only one entry is allowed per trend signal
Re-entries do not happen until the entire trend condition resets
The Strategy Tester remains clean, without duplicate overlapping trades
This eliminates revenge trades, repeated fills, and choppy overtrading.
📌 Dynamic Supertrend Trailing Stop
Stop Loss is anchored to current Supertrend value, creating:
Automatic trailing
Tight downside control
Protection against deep pullbacks
High responsiveness during volatility expansions
📌 Precision Take-Profit (4% Run-Up Capture)
A dedicated global exit block ensures:
Take Profit triggers exactly at 4% price run-up
Uses strategy.exit() with limit orders to catch spikes (wicks)
Works consistently on all timeframes & assets
📌 Automated Position Sizing (2% Risk Default)
Position size is dynamically calculated based on:
Account Equity
Distance to trailing stop
Configured risk %
This enforces proper risk management without manual adjustments.
📈 How to Interpret Results
Reliable Exits: All exits are globally managed, so stops and take profits trigger accurately on every bar.
Clean Trade History: Because of single-entry logic, backtests show one trade per valid signal.
Consistency: Multi-timeframe logic ensures only high-quality, structured trades.
