QQE MOD + SSL Hybrid + Waddah Attar Explosion IndicatorINDICATOR PURPOSE
This indicator is designed to complement my original QQE MOD + SSL Hybrid + Waddah Attar Explosion strategy.
Multiple users have requested that I convert the strategy to an indicator because alertconditions do not work on strategies and people want to specific set alerts for BUY, SELL, CLOSE BUY and CLOSE SELL. This can only be achieved using alertcondition().
This indicator functions in the exact same way as the strategy, but it doesn't have any backtesting functionality. I recomment that you use the original QQE MOD + SSL Hybrid + Waddah Attar Explosion strategy for parameter tuning and backtesting, then if you need more control on alerts you can use this indicator for that purpose.
Only other difference is that I have added grey exit labels on the chart since it's not obvious where the exits would happen like it was in the strategy version.
CREDITS
QQE MOD byMihkel00
SSL Hybrid by Mihkel00
Waddah Attar Explosion by shayankm
Cari dalam skrip untuk "backtesting"
Monthly Performance Table by Dr. MauryaWhat is this ?
This Strategy script is not aim to produce strategy results but It aim to produce monthly PnL performance Calendar table which is useful for TradingView community to generate a monthly performance table for Own strategy.
So make sure to read the disclaimer below.
Why it is required to publish?:
I am not satisfied with the monthly performance available on TV community script. Sometimes it is very lengthy in code and sometimes it showing the wrong PNL for current month.
So I have decided to develop new Monthly performance or return in value as well as in percentage with highly flexible to adjust row automatically.
Features :
Accuracy increased for current month PnL.
There are 14 columns and automatically adjusted rows according to available trade years/month.
First Column reflect the YEAR, from second column to 13 column reflect the month and 14 column reflect the yearly PnL.
In tabulated data reflects the monthly PnL (value and (%)) in month column and Yearly PnL (value and (%)) in Yearly column.
Various color input also added to change the table look like background color, text color, heading text color, border color.
In tabulated data, background color turn green for profit and red for loss.
Copy from line 54 to last line as it is in your strategy script.
Credit: This code is modified and top up of the open-source code originally written by QuantNomad. Thanks for their contribution towards to give base and lead to other developers. I have changed the way of determining past PnL to array form and keep separated current month and year PnL from array. Which avoid the false pnl in current month.
Strategy description:
As in first line I said This strategy is aim to provide monthly performance table not focused on the strategy. But it is necessary to explain strategy which I have used here. Strategy is simply based on ADX available on TV community script. Long entry is based on when the difference between DIPlus and ADX is reached on certain value (Set value in Long difference in Input Tab) while Short entry is based on when the difference between DIMinus and ADX is reached on certain value (Set value in Short difference in Input Tab).
Default Strategy Properties used on chart(Important)
This script backtest is done on 1 hour timeframe of NSE:Reliance Inds Future cahrt, using the following backtesting properties:
Balance (default): 500 000 (default base currency)
Order Size: 1 contract
Comission: 20 INR per Order
Slippage: 5 tick
Default setting in Input tab
Len (ADX length) : 14
Th (ADX Threshhold): 20
Long Difference (DIPlus - ADX) = 5
Short Difference (DIMinus - ADX) = 5
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from the strategies built are realistic.
Disclaimer:
This script not provide indicative of any future results.
This script don’t provide any financial advice.
This strategy is only for the readymade snippet code for monthly PnL performance calender table for any own strategy.
MACD_RSI_trend_followingINFO:
This indicator can be used to build-up a strategy for trading of assets which are currently in trending phase.
My preference is to use it on slowly moving assets like GOLD and on higher timeframes, but practice may show that we find more usefull cases.
This script uses two indicators - MACD and RSI, as the timeframe that those are extracted for is configurable (defaults with the Chart TF, but can be any other selected by the user).
The strategy has the following simple idea - buy if any if the conditions below is true:
The selected TF MACD line crosses above the signal line and the TF RSI is above the user selected trigger value
The selected TF MACD line is above the signal line and the TF RSI crosses above the user selected trigger value
Once we're in position we wait for the selected TF MACD line to cross below the signal line, and then we set a SL at the low of that bar
DETAILS and USAGE:
In the current implementation I find two possible use cases for the indicator:
as a stand-alone indicator on the chart which can also fire alerts that can help to determine if we want to manually enter/exit trades based on them
can be used to connect to the Signal input of the TTS (TempalteTradingStrategy) by jason5480 in order to backtest it, thus effectively turning it into a strategy (instructions below in TTS CONNECTIVITY section)
In the example below we see a position opened at the bar after the buy indicator from the script has been triggered, and then later after the SL indicator from the script has been triggered a SL has been set on the lower wick of the closing candle, and the position eventually got closed once the price hit that level. Note that most of the drawing on the example snapshot below are from the TTS indicator following the buy/sell/SL conditions themseves:
Trading period can be selected from the indicator itself to limit to more interesting periods.
Arrow indications are drawn on the chart to indicate the trading conditions met in the script - green arrow for a buy signal indication and orange for LTF crossunder to indicate setting of SL.
SETTINGS:
Leaving all of the settings as in vanilla use case, as both the MACD and RSI indicator's settings follow the default ones for the stand-alone indicators themselves.
The start-end date is a time filter that can be extermely usefull when backtesting different time periods.
Pesonal preference is using the script on a D/W timeframe, while the indicator is configured to use Monthly chart.
The default value of the RSI filter is left to 50, which can be changed. I.e. if the RSI is above 50 we have a regime filter based on the MACD criteria.
EXTERNAL LIBRARIES:
The script uses a couple of external libraries:
HeWhoMustNotBeNamed/enhanced_ta/14 - collection of TA indicators
jason5480/tts_convention/3 - more details about the Template Trading Strategy below
I would like to highly appreciate and credit the work of both HeWhoMustNotBeNamed and jason5480 for providing them to the community.
TTS SETTINGS (NEEDED IF USED TO BACKTEST WITH TTS):
The TempalteTradingStrategy is a strategy script developed in Pine by jason5480, which I recommend for quick turn-around of testing different ideas on a proven and tested framework
I cannot give enough credit to the developer for the efforts put in building of the infrastructure, so I advice everyone that wants to use it first to get familiar with the concept and by checking
by checking jason5480's profile www.tradingview.com
The TTS itself is extremely functional and have a lot of properties, so its functionality is beyond the scope of the current script -
Again, I strongly recommend to be thoroughly epxlored by everyone that plans on using it.
In the nutshell it is a script that can be feed with buy/sell signals from an external indicator script and based on many configuration options it can determine how to execute the trades.
The TTS has many settings that can be applied, so below I will cover only the ones that differ from the default ones, at least according to my testing - do your own research, you may find something even better :)
The current/latest version that I've been using as of writing and testing this script is TTSv48
Settings which differ from the default ones:
from - False (time filter is from the indicator script itself)
Deal Conditions Mode - External (take enter/exit conditions from an external script)
🔌Signal 🛈➡ - MACD_RSI_trend_following: 🔌Signal to TTSv48 (this is the output from the indicator script, according to the TTS convention)
Sat/Sun - true (for crypto, in order to trade 24/7)
Order Type - STOP (perform stop order)
Distance Method - HHLL (HigherHighLowerLow - in order to set the SL according to the strategy definition from above)
The next are just personal preferenes, you can feel free to experiment according to your trading style
Take Profit Targets - 0 (either 100% in or out, no incremental stepping in or out of positions)
Dist Mul|Len Long/Short- 10 (make sure that we don't close on profitable trades by any reason)
Quantity Method - EQUITY (personal backtesting preference is to consider each backtest as a separate portfolio, so determine the position size by 100% of the allocated equity size)
Equity % - 100 (note above)
Dual_MACD_trendingINFO:
This indicator is useful for trending assets, as my preference is for low-frequency trading, thus using BTCUSD on 1D/1W chart
In the current implementation I find two possible use cases for the indicator:
- as a stand-alone indicator on the chart which can also fire alerts that can help to determine if we want to manually enter/exit trades based on the signals from it (1D/1W is good for non-automated trading)
- can be used to connect to the Signal input of the TTS (TempalteTradingStrategy) by jason5480 in order to backtest it, thus effectively turning it into a strategy (instructions below in TTS CONNECTIVITY section)
Trading period can be selected from the indicator itself to limit to more interesting periods.
Arrow indications are drawn on the chart to indicate the trading conditions met in the script - light green for HTF crossover, dark green for LTF crossover and orange for LTF crossunder.
Note that the indicator performs best in trending assets and markets, and it is advisable to use additional indicators to filter the trading conditions when market/asset is expected to move sideways.
DETAILS:
It uses a couple of MACD indicators - one from the current timeframe and one from a higher timeframe, as the crossover/crossunder cases of the MACD line and the signal line indicate the potential entry/exit points.
The strategy has the following flow:
- If the weekly MACD is positive (MACD line is over the signal line) we have a trading window.
- If we have a trading window, we buy when the daily macd line crosses AND closes above the signal line.
- If we are in a position, we await the daily MACD to cross AND close under the signal line, and only then place a stop loss under the wick of that closing candle.
The user can select both the higher (HTF) and lower (LTF) timeframes. Preferably the lower timeframe should be the one that the Chart is on for better visualization.
If one to decide to use the indicator as a strategy, it implements the following buy and sell criterias, which are feed to the TTS, but can be also manually managed via adding alerts from this indicator.
Since usually the LTF is preceeding the crossover compared to the HTF, then my interpretation of the strategy and flow that it follows is allowing two different ways to enter a trade:
- crossover (and bar close) of the macd over the signal line in the HIGH TIMEFRAME (no need to look at the LOWER TIMEFRMAE)
- crossover (and bar close) of the macd over the signal line in the LOW TIMEFRAME, as in this case we need to check also that the macd line is over the signal line for the HIGH TIMEFRAME as well (like a regime filter)
The exit of the trade is based on the lower timeframe MACD only, as we create a stop loss equal to the lower wick of the bar, once the macd line crosses below the signal line on that timeframe
SETTINGS:
All of the indicator's settings are for the vanilla/general case.
User can set all of the MACD parameters for both the higher and lower (current) timeframes, currently left to default of the MACD stand-alone indicator itself.
The start-end date is a time filter that can be extermely usefull when backtesting different time periods.
TTS SETTINGS (NEEDED IF USED TO BACKTEST WITH TTS)
The TempalteTradingStrategy is a strategy script developed in Pine by jason5480, which I recommend for quick turn-around of testing different ideas on a proven and tested framework
I cannot give enough credit to the developer for the efforts put in building of the infrastructure, so I advice everyone that wants to use it first to get familiar with the concept and by checking
by checking jason5480's profile www.tradingview.com
The TTS itself is extremely functional and have a lot of properties, so its functionality is beyond the scope of the current script -
Again, I strongly recommend to be thoroughly epxlored by everyone that plans on using it.
In the nutshell it is a script that can be feed with buy/sell signals from an external indicator script and based on many configuration options it can determine how to execute the trades.
The TTS has many settings that can be applied, so below I will cover only the ones that differ from the default ones, at least according to my testing - do your own research, you may find something even better :)
The current/latest version that I've been using as of writing and testing this script is TTSv48
Settings which differ from the default ones:
- from - False (time filter is from the indicator script itself)
- Deal Conditions Mode - External (take enter/exit conditions from an external script)
- 🔌Signal 🛈➡ - Dual_MACD: 🔌Signal to TTSv48 (this is the output from the indicator script, according to the TTS convention)
- Sat/Sun - true (for crypto, in order to trade 24/7)
- Order Type - STOP (perform stop order)
- Distance Method - HHLL (HigherHighLowerLow - in order to set the SL according to the strategy definition from above)
The next are just personal preferenes, you can feel free to experiment according to your trading style
- Take Profit Targets - 0 (either 100% in or out, no incremental stepping in or out of positions)
- Dist Mul|Len Long/Short- 10 (make sure that we don't close on profitable trades by any reason)
- Quantity Method - EQUITY (personal backtesting preference is to consider each backtest as a separate portfolio, so determine the position size by 100% of the allocated equity size)
- Equity % - 100 (note above)
EXAMPLES:
If used as a stand-alone indicator, the green arrows on the bottom will represent:
- light green - MACD line crossover signal line in the HTF
- darker green - MACD line crossover signal line in the LTF
- orange - MACD line crossunder signal line in the LTF
I recommend enabling the alerts from the script to cover those cases.
If used as an input to the TTS, we'll get more decorations on the chart from the TTS itself.
In the example below we open a trade on the next day of LTF crossover, then a few days later a crossunder in the LTF occurs, so we set a SL at the low of the wick of this day. Few days later the price doesn't recover and hits that SL, so the position is closed.
[blackcat] L2 Zero Lag Hull Moving AverageZero Lag Hull Moving Average (ZLHMA) is a technical indicator that is based on the principles of Zero Lag Hull Moving Average (HMA). It is designed to provide a smoother and more accurate representation of price trends by reducing lag and improving the responsiveness of the moving average line.
Compared to traditional moving average lines, the Zero Lag Hull Moving Average has the advantage of being able to capture price trend changes more precisely. It achieves this by utilizing a higher degree of smoothness through the use of weighted moving averages, and by incorporating the calculation method of Hull Moving Average (HMA) to further eliminate lag.
The calculation process of the Zero Lag Hull Moving Average involves two main steps. First, the Hull Moving Average (HMA) is calculated by taking the difference between two weighted moving averages applied to the price data. This helps to smooth out the price fluctuations and reduce lag. Then, the difference between two weighted moving averages is applied once again to the HMA, resulting in the Zero Lag Hull Moving Average. This final step further enhances the accuracy and timeliness of the indicator.
The Zero Lag Hull Moving Average offers several advantages for traders. Firstly, it provides a quicker response to changes in price trends, allowing traders to make more timely and informed trading decisions. This can be particularly useful in fast-moving markets where speed is crucial. Secondly, by reducing lag, the Zero Lag Hull Moving Average helps traders avoid missing important market signals and potential trading opportunities. It provides a more accurate representation of the current market conditions, enabling traders to act with greater confidence.
However, it is important to note that the Zero Lag Hull Moving Average should not be used as the sole basis for making trading decisions. It is recommended to consider other technical indicators, as well as fundamental and market analysis, to gain a comprehensive understanding of the market dynamics. Traders should also conduct thorough backtesting and validation of their trading strategies to ensure their effectiveness.
In conclusion, the Zero Lag Hull Moving Average is a powerful tool that can enhance the accuracy and responsiveness of technical analysis. By reducing lag and providing a more accurate representation of price trends, it can assist traders in making better-informed trading decisions. However, it should be used in conjunction with other indicators and analysis methods for a comprehensive approach to trading.
Please note that the information provided by blackcat1402 is for educational purposes only and should not be considered as financial advice. It is essential to conduct thorough research, backtesting, and validation before implementing any trading strategies.
[tradinghook] - Renko Trend Reversal Strategy V2Title: Renko Trend Reversal Strategy
Short Title: - Renko TRS
> Special thanks to for manually calculating `renkoClose` and `renkoOpen` values in order to remove the infamous repaint issue
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
[tradinghook] - Renko Trend Reversal Strategy - Renko Trend Reversal Strategy
Short Title: - Renko TRS
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
Ultimate Balance StrategyThe Ultimate Balance Oscillator Strategy harnesses the power of the Ultimate Balance Oscillator to deliver a comprehensive and disciplined approach to trading. By combining the insights of the Rate of Change (ROC), Relative Strength Index (RSI), Commodity Channel Index (CCI), Williams Percent Range, and Average Directional Index (ADX) from TradingView, this strategy offers traders a systematic way to navigate the markets with precision.
The core principle of this strategy lies in its ability to identify optimal entry and exit points based on the movement of the Ultimate Balance Oscillator. When the oscillator line crosses below the 0.75 level, a buy signal is generated, indicating a potential opportunity for a bullish trend reversal. Conversely, when the oscillator line crosses above the 0.25 level, it triggers an exit signal, suggesting a possible end to a bullish trend.
Key Features:
1. Objective Market Analysis: The Ultimate Balance Oscillator Strategy provides a disciplined and objective approach to market analysis. By relying on the quantified insights of multiple indicators, it helps traders cut through market noise and focus on key signals, improving decision-making and reducing emotional biases.
2. Enhanced Timing and Precision: This strategy's entry and exit signals are based on the specific thresholds of the Ultimate Balance Oscillator. By waiting for confirmation through the crossing of these levels, traders can potentially enter trades at opportune moments and exit with greater precision, maximizing profit potential and minimizing risk exposure.
3. Customizability and Adaptability: The strategy offers flexibility, allowing traders to customize the parameters to fit their preferred trading style and timeframes. Whether you're a short-term trader or a long-term investor, the Ultimate Balance Oscillator Strategy can be adjusted to suit your specific needs, making it adaptable to various market conditions.
4. Real-time Alerts: Stay informed and never miss a potential trade opportunity with the strategy's built-in alert system. Set personalized alerts for buy and exit signals to receive timely notifications, ensuring you're always aware of the latest developments in the market.
5. Backtesting and Optimization: Before applying the strategy to live trading, it's recommended to conduct thorough backtesting and optimization. By testing the strategy's performance over historical data and fine-tuning the parameters, you can gain insights into its strengths and weaknesses, enabling you to make informed adjustments and increase its effectiveness.
Trading involves risk. Use the Ultimate Balance Oscillator Strategy at your own discretion. Past performance is not indicative of future results.
Bollinger Bands - Breakout StrategyThe Bollinger Bands - Breakout Strategy is a trend-following optimized for short-term trading in the crypto market. This strategy employs the Bollinger Bands, a widely recognized technical indicator, as its primary instrument for pinpointing potential trades. It is capable of executing both long and short positions, depending on whether the market is in a spot or futures, and is particularly effective in trending markets.
The strategy boasts a high degree of configurability, allowing users to set the Bollinger Bands period and deviation, trend filter, volatility filter, trade direction filter, rate of change filter, and date filter. Furthermore, it offers options for Take Profit, Stop Loss, and Trailing Stop for both long and short positions, ensuring a comprehensive risk management approach. The inclusion of a maximum intraday loss feature adds another layer of protection, making this strategy a valuable tool for traders seeking a professional and adaptable trading system.
Name : Bollinger Bands - Breakout Strategy
Category : Trend Follower based on Bollinger Bands
Operating mode : Long and Short on Futures or Long on Spot
Trade duration : Intraday
Timeframe : 2H, 3H, 4H, 5H
Market : Crypto
Suggested usage : Trending Markets
Entry : When the price crosses above or below the Bollinger Bands
Exit : Opposite Cross or Profit target, Trailing stop or Stop loss
Configuration :
- Bollinger Bands period and deviation
- Trend Filter
- Volatility Filter
- Trade direction filter
- Rate of Change filter
- Date Filter (for backtesting purposes)
- Take Profit, Stop Loss and Trailing Stop for long and short positions
- Risk Management: Max Intraday Loss
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: BTCUSDT.P
⁃ Timeframe: 4H
⁃ Fee: 0.025%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2019-09-19 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits :
- LucF of Pine Coders for f_security function to avoid repainting using security.
- QuantNomad for Monthly Table.
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Divergences in 52 Week Moving Averages, Adjusted and SmoothedThis script description is intended to be holistic and comprehensive for the understanding of the interested parties who view the script.
Following the PineCoders suggestions, I have provided detailed breakdowns both within the code and in the description immediately below:
► Description
This description is intended to be detailed and meaningful, conveying the understanding of the script’s intention to the user:
The theory: Divergences and extreme readings in 52-Week highs on major indexes can provide a view into a potential pending move in the opposite direction of how the market has been trending. By comparing the 52-Week Hi/Lo indices and applying an Exponential Moving Average (EMA), we can assess how extreme a move is from the average. If the move provides an extreme reading, it would potentially be beneficial to “fade” the move (take a position in the opposing direction).
The intention: The intentionality of this script is to provide a visualization of when the highly-probable opportunity to fade over a multi-day or multi-week period arises. In addition to this, based on backtesting prior moves and reading the various levels of significant reversals, three tiers: “Standard”, “Sensitive”, and “Highly Sensitive” have been applied, the user can choose which sensitivity level they would like to see, there are far less false positives on the Standard and Sensitive settings, while Highly Sensitive often signals multiple times with the move coming a few days later.
The application: The settings allow the user to customize their sensitivity to the fade signals, with the ability to customize the visual that shows up as well. For higher-highs that are fade-worthy, the signal will appear on the top of the candle, for lower-lows that are fade-worthy, the signal will appear on the bottom of the candle. The users risk criteria should be the primary driver of the entry/exit, although when backtesting it appears that the significant move is typically completed within a 2-4 week period at max and 3-5 day period at minimum.
A personal note: I am a futures trader intraday but would very strongly caution users when using this strategy with futures (unless their risk tolerance is higher than most). The most beneficial strategy when fading moves would be to enter in tranches, starting at the first signal and adding on any pullback (as long as the pullback is not below the initial entry point). 1-6 Week Date-To-Expiry options would be the primary method for applying this strategy. I would also like to add that SPY/SPX options (SPDR S&P 500 ETF Trust / CBOE S&P 500 Index) are the most liquid options that could be applied in this strategy.
► Description (additional)
With the understanding that few users can read pinescript (Pine), the description above contains all of the necessary information that is necessary for a user to understand the intention for script utilization. For those who do understand Pine, the code is commented in each section in order to provide an understanding of the underlying functions, calculations, and thought process that went on during the writing of the script.
► Description (additional)
This script’s description contains no delegations, all aspects of the script as well as the initial idea behind it are contained in the description above, which is self-contained in it’s entirety with a clear and defined purpose that is written with the intent to holistically capture the intent of the potential use for this indicator.
► General House Rule #2
This script and the description (as well as my profile) contain no links or associations to promotion of any kind, I am not a business, I am not an individual that will in any way make money from this script or the promotion of another person, idea, company, entity, or legal persons (foreign or domestic).
► Originality and usefulness
This is an original and custom script (and idea) that is not a rehashing or a copy of any code from any other programmers in the tradingview community.
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
Drip's 11am rule breakout/breakdown (OG)This indicator is based on Drippy2hard's 11:30 am (EST) rule.
In simple terms the rule states that:
If a trending stock makes a new high after 11:15-11:30am EST, there is a 75% chance of closing within 1% of High of day (HOD). Same applies for downtrend.
Please note:
Not all stocks will abide by this, this is backtested on stocks with avg daily volume > 2M and mostly mega cap stocks which have liquid option chains. The backtesting results show very promising results on $SPY/ $SPX so it is advised to trade $SPY/ $SPX using this indicator over any other stocks.
Although the name suggests 11 AM rule, the backtesting shows higher win rate for 11:30 AM so please select that option in the settings.
As always, no indicator is perfect and please follow your risk management and understand that indicators are tools to aid your trading and by no means they are supposed to work as intended in all scenarios
How the script works
1. A HOD/LOD zone is identified based on regular session (9:30am-11:30am) EST. Users can select cut off time to 11AM in the settings. These will be indicated on chart after 11/11:30pm depending on what user selected
2. If the stock breaks above the HOD and the ADX is showing strong momentum to upside then the candlesticks will start showing neon color, if the trend based on moving averages and candle closing is also bullish then the indicator will show trend arrows under the candle indicating to stay in the trade. Same applies for break below LOD, only the colors will change to represent downtrend.
3. An optional cloud is also shown if the trend is developed. The cloud can be used as trail stop or re entry point as long as it is displayed on chart
How to use the indicator in trading
In general, there are three scenarios which are trade worthy
1. If the stocks breaks out above the HOD zone and up trend develops or the stocks breaks below the LOD zone and downtrend develops. See images below
2. You can also use the LOD/HOD zone as demand/ supply if the Price action is range bound like this example below
Thanks for reading, please give thumbs up if you like using it! Please post comments on how to use it.
Pure Mark Minervini 10%TP 5%CLBacktesting Mark Miniverni Template
By Donnie Lee
Overall, a good basic guideline from Mark Miniverni to choose which stock to buy. His selection are said to be stocks in stage 2 uptrend phase which could see price surge soon.
This script enable backtesting of Mark template (Investor's Business Ranking Excluded) on equity like stocks
Further fine tuning with additional filters are needed to find good entry with desired cut loss level and position sizing.
There is no holy grail strategy. Choose one with an edge that you are comfortable with and stick to it.
Losing is part and parcel of trading. Hesitation to cut loss can lead to big loss. And if you can avoid losing big, you might stand a chance to profit in the end.
Mark Miniverni Template
1. The current stock price is above both the 150-day (30-week) and the 200-day (40-week) moving average price lines.
2. The 150-day moving average is above the 200-day moving average.
3. The 200-day moving average line is trending up for at least 1 month (preferably 4–5 months minimum in most cases).
4. The 50-day (10-week) moving average is above both the 150-day and 200-day moving averages.
5. The current stock price is trading above the 50-day moving average.
6. The current stock price is at least 25% above its 52-week low (30% as per his book 'Trade Like a Stock Market Wizard').
7. The current stock price is within at least 25% of its 52-week high (the closer to a new high the better).
Heikin Ashi SupertrendAbout this Strategy
This supertrend strategy uses the Heikin Ashi candles to generate the supertrend but enters and exits trades using normal candle close prices. If you use the standard built in Supertrend indicator on Heikin Ashi candles, it will produce very unrealistic backtesting results because it uses the Heikin Ashi prices instead of the real prices. However, by signaling the supertrend reversals using Heikin Ashi while using standard candle close prices for the entries and exits, it corrects the backtesting errors and gives you a more realistic equity curve. You should set the chart to use standard candles and then hide them (the strategy creates the candles).
This strategy includes:
Plotting of Heikin Ashi candles
Heikin Ashi Supertrend
Long and Short Entry Signals
Move stop loss after trade is X% in profit
Profit Target
Stop Loss
Built in Alertatron automation
Alertatron Trade Automation Integration
For Alertatron integration, be sure to configure the strategy settings and "Enable Webhook Messages" before creating an alert with {{strategy.order.alert_message}} in the body of your alert message. Be sure to enable webhooks and point it to your Incoming Alertatron webhook URL.
Notes
While this strategy does pretty well during trending markets, It's worth noting that the Buy and Hold ROI is much better during peak times of the bull market
Not financial advice. Do not risk more than you can afford to lose.
Strategy BackTest Display Statistics - TraderHalaiThis script was born out of my quest to be able to display strategy back test statistics on charts to allow for easier backtesting on devices that do not natively support backtest engine (such as mobile phones, when I am backtesting from away from my computer). There are already a few good ones on TradingView, but most / many are too complicated for my needs.
Found an excellent display backtest engine by 'The Art of Trading'. This script is a snippet of his hard work, with some very minor tweaks and changes. Much respect to the original author.
Full credit to the original author of this script. It can be found here: www.tradingview.com
I decided to modify the script by simplifying it down and make it easier to integrate into existing strategies, using simple copy and paste, by relying on existing tradingview strategy backtester inputs. I have also added 3 additional performance metrics:
- Max Run Up
- Average Win per trade
- Average Loss per trade
As this is a work in progress, I will look to add in more performance metrics in future, as I further develop this script.
Feel free to use this display panel in your scripts and strategies.
Thanks and enjoy :)
Short Swing Bearish MACD Cross (By Coinrule)This strategy is oriented towards shorting during downside moves, whilst ensuring the asset is trading in a higher timeframe downtrend, and exiting after further downside.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to hodl this cash, or use it to reinvest when the market reaches attractive buying levels. Alternatively, you can use this when trading contracts on futures markets where there is no need to already own the underlying asset prior to shorting it.
ENTRY
This script utilises the MACD indicator accompanied by the Exponential Moving Average (EMA) 450 to enter trades. The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 11-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9.
The EMA 450 is used as additional confirmation to prevent the script from shorting when price is above this long-term moving average. Once price is above the EMA 450 the script will not open any shorts - preventing the rule from attempting to short uptrends. Due to this, this strategy is ideal for setting and forgetting.
The script will enter trades based on two conditions:
1) When the MACD signals a bearish cross. This occurs when the EMA 11 crosses below the EMA 26 within the MACD signalling the start of a potential downtrend.
2) Price has closed below the EMA 450. Price closing below this long-term EMA signals that the asset is in a sustained downtrend. Price breaking above this could indicate a bullish strength in which shorting would not be profitable.
EXIT
This script utilises a set take-profit and stop-loss from the entry of the trade. The take profit is set at 8% and the stop loss of 4%, providing a risk reward ratio of 2. This indicates the script will be profitable if it has a win ratio greater than 33%.
Take-Profit Exit: -8% price decrease from entry price.
OR
Stop-Loss Exit: +4% price increase from entry price.
Based on backtesting results across a selection of assets, the 45-minute and 1-hour timeframes are the best for this strategy.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
The backtesting data was recorded from December 1st 2021, just as the market was beginning its downtrend. We therefore recommend analysing the market conditions prior to utilising this strategy as it operates best on weak coins during downtrends and bearish conditions, however the EMA 450 condition should mitigate entries during bullish market conditions.
Oversold RSI with tight SL Strategy (by Coinrule)This is one of the best strategies that can be used to get familiar with technical indicators and start to include them in your trading bot rules.
ENTRY
1. This trading system uses the RSI ( Relative Strength Index ) to anticipate good points to enter positions. RSI is a technical indicator frequently used in trading. It works by measuring the speed and change of price movements to determine whether a coin is oversold (indicating a good entry point) or overbought (indicating a point of exit/entry for a short position). The RSI oscillates between 0 and 100 and is traditionally considered overbought when over 70 and oversold when below 30.
2. To pick the right moment to buy, the strategy enters a trade when the RSI falls below 30 indicating the coin is oversold and primed for a trend reversal.
EXIT
The strategy then exits the position when the price appreciates 7% from the point of entry. The position also maintains a tight stop-loss and closes the position if the price depreciates 1% from the entry price. The idea behind this is to cut your losing trades fast and let your winners ride.
The best time frame for this strategy based on our backtesting data is the daily. Shorter time frames can also work well on certain coins, however in our experience, the daily works best. Feel free to experiment with this script and test it on a variety of your coins! With our backtesting data a trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume. In the example shown, this strategy made a handsome net profit of 39.31% on Chainlink with 61.54% of trades being profitable.
EMA bands + leledc + bollinger bands trend following strategy v2The basics:
In its simplest form, this strategy is a positional trend following strategy which enters long when price breaks out above "middle" EMA bands and closes or flips short when price breaks down below "middle" EMA bands. The top and bottom of the middle EMA bands are calculated from the EMA of candle highs and lows, respectively.
The idea is that entering trades on breakouts of the high EMAs and low EMAs rather than the typical EMA based on candle closes gives a bit more confirmation of trend strength and minimizes getting chopped up. To further reduce getting chopped up, the strategy defaults to close on crossing the opposite EMA band (ie. long on break above high EMA middle band and close below low EMA middle band).
This strategy works on all markets on all timeframes, but as a trend following strategy it works best on markets prone to trending such as crypto and tech stocks. On lower timeframes, longer EMAs tend to work best (I've found good results on EMA lengths even has high up to 1000), while 4H charts and above tend to work better with EMA lengths 21 and below.
As an added filter to confirm the trend, a second EMA can be used. Inputting a slower EMA filter can ensure trades are entered in accordance with longer term trends, inputting a faster EMA filter can act as confirmation of breakout strength.
Bar coloring can be enabled to quickly visually identify a trend's direction for confluence with other indicators or strategies.
The goods:
Waiting for the trend to flip before closing a trade (especially when a longer base EMA is used) often leaves money on the table. This script combines a number of ways to identify when a trend is exhausted for backtesting the best early exits.
"Delayed bars inside middle bands" - When a number of candle's in a row open and close between the middle EMA bands, it could be a sign the trend is weak, or that the breakout was not the start of a new trend. Selecting this will close out positions after a number of bars has passed
"Leledc bars" - Originally introduced by glaz, this is a price action indicator that highlights a candle after a number of bars in a row close the same direction and result in greatest high/low over a period. It often triggers when a strong trend has paused before further continuation, or it marks the end of a trend. To mitigate closing on false Leledc signals, this strategy has two options: 1. Introducing requirement for increased volume on the Leledc bars can help filter out Leledc signals that happen mid trend. 2. Closing after a number of Leledc bars appear after position opens. These two options work great in isolation but don't perform well together in my testing.
"Bollinger Bands exhaustion bars" - These bars are highlighted when price closes back inside the Bollinger Bands and RSI is within specified overbought/sold zones. The idea is that a trend is overextended when price trades beyond the Bollinger Bands. When price closes back inside the bands it's likely due for mean reversion back to the base EMA in which this strategy will ideally re-enter a position. Since the added RSI requirements often make this indicator too strict to trigger a large enough sample size to backtest, I've found it best to use "non-standard" settings for both the bands and the RSI as seen in the default settings.
"Buy/Sell zones" - Similar to the idea behind using Bollinger Bands exhaustion bars as a closing signal. Instead of calculating off of standard deviations, the Buy/Sell zones are calculated off multiples of the middle EMA bands. When trading beyond these zones and subsequently failing back inside, price may be due for mean reversion back to the base EMA. No RSI filter is used for Buy/Sell zones.
If any early close conditions are selected, it's often worth enabling trade re-entry on "middle EMA band bounce". Instead of waiting for a candle to close back inside the middle EMA bands, this feature will re-enter position on only a wick back into the middle bands as will sometimes happen when the trend is strong.
Any and all of the early close conditions can be combined. Experimenting with these, I've found can result in less net profit but higher win-rates and sharpe ratios as less time is spent in trades.
The deadly:
The trend is your friend. But wouldn't it be nice to catch the trends early? In ranging markets (or when using slower base EMAs in this strategy), waiting for confirmation of a breakout of the EMA bands at best will cause you to miss half the move, at worst will result in getting consistently chopped up. Enabling "counter-trend" trades on this strategy will allow the strategy to enter positions on the opposite side of the EMA bands on either a Leledc bar or Bollinger Bands exhaustion bar. There is a filter requiring either a high/low (for Leledc) or open (for BB bars) outside the selected inner or outer Buy/Sell zone. There are also a number of different close conditions for the counter-trend trades to experiment with and backtest.
There are two ways I've found best to use counter-trend trades
1. Mean reverting scalp trades when a trend is clearly overextended. Selecting from the first 5 counter-trend closing conditions on the dropdown list will usually close the trades out quickly, with less profit but less risk.
2. Trying to catch trends early. Selecting any of the close conditions below the first 5 can cause the strategy to behave as if it's entering into a new trend (from the wrong side).
This feature can be deadly effective in profiting from every move price makes, or deadly to the strategy's PnL if not set correctly. Since counter-trend trades open opposite the middle bands, a stop-loss is recommended to reduce risk. If stop-losses for counter-trend trades are disabled, the strategy will hold a position open often until liquidation in a trending market if th trade is offsides. Note that using a slower base EMA makes counter-trend stop-losses even more necessary as it can reduce the effectiveness of the Buy/Sell zone filter for opening the trades as price can spend a long time trending outside the zones. If faster EMAs (34 and below) are used with "Inner" Buy/Zone filter selected, the first few closing conditions will often trigger almost immediately closing the trade at a loss.
The niche:
I've added a feature to default into longs or shorts. Enabling these with other features (aside from the basic long/short on EMA middle band breakout) tends to break the strategy one way or another. Enabling default long works to simulate trying to acquire more of the asset rather than the base currency. Enabling default short can have positive results for those high FDV, high inflation coins that go down-only for months at a time. Otherwise, I use default short as a hedge for coins that I hold and stake spot. I gain the utility and APR of staking while reducing the risk of holding the underlying asset by maintaining a net neutral position *most* of the time.
Disclaimer:
This script is intended for experimenting and backtesting different strategies around EMA bands. Use this script for your live trading at your own risk. I am a rookie coder, as such there may be errors in the code that cause the strategy to behave not as intended. As far as I can tell it doesn't repaint, but I cannot guarantee that it does not. That being said if there's any question, improvements, or errors you've found, drop a comment below!
GRID SPOT TRADING ALGORITHM - GRID BOT TRADING STRATEGYGRID SPOT TRADING ALGORITHM : LONG ONLY STRATEGY OPEN SOURCE
This is a long only strategy for spot assets.
HOW IT WORKS
Grid trading is a trading strategy where an investor creates a so-called "price grid". The basic idea of the strategy is to repeatedly buy at the pre-specified price and then wait for the price to rise above that level and then sell the position (and vice versa with shorting or hedging).
FEATURES
Grids: This algorithm has a total of 10 grids.
Take profit: The trader can increase or decrease the distance between the grids from the User Interface panel, the distance between one grid and another represents the take profit.
Management: The algorithm buys 10% of the capital every time the price breaks down a grid and sells during a rise to the next higher grid. The initial capital is invested in 10 sizes which represent 10% of the capital per trade.
Stop Loss: The algorithm knows no stop loss as long as it is not activated from the User Interface panel. By activating the stop loss from the User Interface panel the algorithm will insert a close condition on all trades which will be calculated from the last lower grid.
Trades: Trades are opened only if the price is within the grid. If the market leaves the grid the algorithm will not buy new positions or sell new positions.
Optimal market conditions: The favorable market for this algorithm is the sideways market.
LIMITATIONS OF THE MODEL
The trader must take into account that this is a static model. It only works perfectly well if the market is in a sideways phase and incurs heavy losses if the market takes a downward trend. The model is unusable for an uptrend. The trader must therefore carefully analyze the market where he intends to use this strategy, making sure that the price is in a sideways phase.
USES
Indispensable research and backtesting tool for those using bots for their investments. The algorithm produces a backtesting of the strategy for past history. It is used by professional traders to understand if this strategy has been profitable on a market and what parameters to use for bots using this strategy (Kucoin, Binance etc.).
If you would like to develop your own algorithm with customized conditions based on a grid strategy, please contact us.
If you need help in using this tool, please contact us without hesitation.
[astropark] Moon Phases [strategy]Dear Followers,
today I'm glad to present you an indicator which calculates Moon Phases and let's you backtest the simplest strategy over it: buy/sell on full moon and do the opposite on new moon.
This is a public free indicator based on the public one by @paaax:
I added my usual backtesting logic, plus some more customization inputs for easy coloring.
The lower the timeframe you backtest on, the more backtesting data are effective.
Enjoy!
-- astropark
MACD Long StratFirst script I've written, but the concept is pretty simple. This uses the MACD with settings fast_SMA = 6 and slow SMA=16 and uses the distance between the 2 (histogram) to look for potential trend reversals to flag potential entries for Long trades. It waits for the confirmation looking backward 2 x timeframes (to reduce false calls slightly). You can adjust it to open / close quicker (1 timeframe instread of 2) but backtesting shows 2 timeframe delay is best to avoid false signals.
The script suggests Long entry points based on this criteria and uses the converse (reducing histogram / SMA difference delayed by 2 timeframes) to suggest exit or trade close points for downward reversal. It was originally written looking at 1m scalps but backtesting shows this is even more effective on higher timeframes (1D).
Delta-RSI Strategy (with filters)Delta-RSI Strategy (with filters):
This is a version of the Delta-RSI Oscillator strategy with several criteria available to filter entry and exit signals. This script is also suitable for backtesting over a user-defined period and offers several risk management options (take profit and stop loss).
Since the publication of the Delta-RSI Oscillator script, I have been asked many times to make it compatible with the Strategy Tester and add filtering criteria to minimize "false" signals. This version covers many of these requests. Feel free to insert your favorite D-RSI parameters and play around!
ABOUT DELTA-RSI
Delta-RSI represents a smoothed time derivative of the RSI designed as a momentum indicator (see links below):
INPUT DESCTIPTION
MODEL PARAMETERS
Polynomial Order : The order of local polynomial used to interpolate the relative strength index (RSI).
Length : The length of the lookback frame where local regression is applied.
RSI Length : The timeframe of RSI used as input.
Signal Length : The signal line is a EMA of the D-RSI time series. This input parameter defines the EMA length.
ALLOWED ENTRIES
The strategy can include long entries, short entries or both.
ENTRY AND EXIT CONDITIONS
Zero-crossing : bullish trade signal triggered when D-RSI crosses zero from negative to positive values (bearish otherwise)
Signal Line Crossing : bullish trade signal triggered when D-RSI crosses from below to above the signal line (bearish otherwise)
Direction Change : bullish trade signal triggered when D-RSI was negative and starts ascending (bearish otherwise)
APPLY FILTERS TO
The filters (described below) can be applied to long entry, short entry and exit signals.
RELATIVE VOLUME FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the current volume is greater than N times the average over the last M bars.
VOLATILITY FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the N-period average true range, ATR, is greater than the M-period ATR. If N < M, this condition implies increasing volatility.
OVERBOUGHT/OVERSOLD FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the value of 14-period RSI is in the range between N and M.
STOP LOSS/TAKE PROFIT
Fixed and trailing stop loss as well as take profit options are available.
FIXED BACKTESTING START/END DATES
If the checkboxes are not checked, the strategy will backtest all available price bars.
`security()` revisited [PineCoders]NOTE
The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work.
█ OVERVIEW
This script presents a new function to help coders use security() in both repainting and non-repainting modes. We revisit this often misunderstood and misused function, and explain its behavior in different contexts, in the hope of dispelling some of the coder lure surrounding it. The function is incredibly powerful, yet misused, it can become a dangerous WMD and an instrument of deception, for both coders and traders.
We will discuss:
• How to use our new `f_security()` function.
• The behavior of Pine code and security() on the three very different types of bars that make up any chart.
• Why what you see on a chart is a simulation, and should be taken with a grain of salt.
• Why we are presenting a new version of a function handling security() calls.
• Other topics of interest to coders using higher timeframe (HTF) data.
█ WARNING
We have tried to deliver a function that is simple to use and will, in non-repainting mode, produce reliable results for both experienced and novice coders. If you are a novice coder, stick to our recommendations to avoid getting into trouble, and DO NOT change our `f_security()` function when using it. Use `false` as the function's last argument and refrain from using your script at smaller timeframes than the chart's. To call our function to fetch a non-repainting value of close from the 1D timeframe, use:
f_security(_sym, _res, _src, _rep) => security(_sym, _res, _src )
previousDayClose = f_security(syminfo.tickerid, "D", close, false)
If that's all you're interested in, you are done.
If you choose to ignore our recommendation and use the function in repainting mode by changing the `false` in there for `true`, we sincerely hope you read the rest of our ramblings before you do so, to understand the consequences of your choice.
Let's now have a look at what security() is showing you. There is a lot to cover, so buckle up! But before we dig in, one last thing.
What is a chart?
A chart is a graphic representation of events that occur in markets. As any representation, it is not reality, but rather a model of reality. As Scott Page eloquently states in The Model Thinker : "All models are wrong; many are useful". Having in mind that both chart bars and plots on our charts are imperfect and incomplete renderings of what actually occurred in realtime markets puts us coders in a place from where we can better understand the nature of, and the causes underlying the inevitable compromises necessary to build the data series our code uses, and print chart bars.
Traders or coders complaining that charts do not reflect reality act like someone who would complain that the word "dog" is not a real dog. Let's recognize that we are dealing with models here, and try to understand them the best we can. Sure, models can be improved; TradingView is constantly improving the quality of the information displayed on charts, but charts nevertheless remain mere translations. Plots of data fetched through security() being modelized renderings of what occurs at higher timeframes, coders will build more useful and reliable tools for both themselves and traders if they endeavor to perfect their understanding of the abstractions they are working with. We hope this publication helps you in this pursuit.
█ FEATURES
This script's "Inputs" tab has four settings:
• Repaint : Determines whether the functions will use their repainting or non-repainting mode.
Note that the setting will not affect the behavior of the yellow plot, as it always repaints.
• Source : The source fetched by the security() calls.
• Timeframe : The timeframe used for the security() calls. If it is lower than the chart's timeframe, a warning appears.
• Show timeframe reminder : Displays a reminder of the timeframe after the last bar.
█ THE CHART
The chart shows two different pieces of information and we want to discuss other topics in this section, so we will be covering:
A — The type of chart bars we are looking at, indicated by the colored band at the top.
B — The plots resulting of calling security() with the close price in different ways.
C — Points of interest on the chart.
A — Chart bars
The colored band at the top shows the three types of bars that any chart on a live market will print. It is critical for coders to understand the important distinctions between each type of bar:
1 — Gray : Historical bars, which are bars that were already closed when the script was run on them.
2 — Red : Elapsed realtime bars, i.e., realtime bars that have run their course and closed.
The state of script calculations showing on those bars is that of the last time they were made, when the realtime bar closed.
3 — Green : The realtime bar. Only the rightmost bar on the chart can be the realtime bar at any given time, and only when the chart's market is active.
Refer to the Pine User Manual's Execution model page for a more detailed explanation of these types of bars.
B — Plots
The chart shows the result of letting our 5sec chart run for a few minutes with the following settings: "Repaint" = "On" (the default is "Off"), "Source" = `close` and "Timeframe" = 1min. The five lines plotted are the following. They have progressively thinner widths:
1 — Yellow : A normal, repainting security() call.
2 — Silver : Our recommended security() function.
3 — Fuchsia : Our recommended way of achieving the same result as our security() function, for cases when the source used is a function returning a tuple.
4 — White : The method we previously recommended in our MTF Selection Framework , which uses two distinct security() calls.
5 — Black : A lame attempt at fooling traders that MUST be avoided.
All lines except the first one in yellow will vary depending on the "Repaint" setting in the script's inputs. The first plot does not change because, contrary to all other plots, it contains no conditional code to adapt to repainting/no-repainting modes; it is a simple security() call showing its default behavior.
C — Points of interest on the chart
Historical bars do not show actual repainting behavior
To appreciate what a repainting security() call will plot in realtime, one must look at the realtime bar and at elapsed realtime bars, the bars where the top line is green or red on the chart at the top of this page. There you can see how the plots go up and down, following the close value of each successive chart bar making up a single bar of the higher timeframe. You would see the same behavior in "Replay" mode. In the realtime bar, the movement of repainting plots will vary with the source you are fetching: open will not move after a new timeframe opens, low and high will change when a new low or high are found, close will follow the last feed update. If you are fetching a value calculated by a function, it may also change on each update.
Now notice how different the plots are on historical bars. There, the plot shows the close of the previously completed timeframe for the whole duration of the current timeframe, until on its last bar the price updates to the current timeframe's close when it is confirmed (if the timeframe's last bar is missing, the plot will only update on the next timeframe's first bar). That last bar is the only one showing where the plot would end if that timeframe's bars had elapsed in realtime. If one doesn't understand this, one cannot properly visualize how his script will calculate in realtime when using repainting. Additionally, as published scripts typically show charts where the script has only run on historical bars, they are, in fact, misleading traders who will naturally assume the script will behave the same way on realtime bars.
Non-repainting plots are more accurate on historical bars
Now consider this chart, where we are using the same settings as on the chart used to publish this script, except that we have turned "Repainting" off this time:
The yellow line here is our reference, repainting line, so although repainting is turned off, it is still repainting, as expected. Because repainting is now off, however, plots on historical bars show the previous timeframe's close until the first bar of a new timeframe, at which point the plot updates. This correctly reflects the behavior of the script in the realtime bar, where because we are offsetting the series by one, we are always showing the previously calculated—and thus confirmed—higher timeframe value. This means that in realtime, we will only get the previous timeframe's values one bar after the timeframe's last bar has elapsed, at the open of the first bar of a new timeframe. Historical and elapsed realtime bars will not actually show this nuance because they reflect the state of calculations made on their close , but we can see the plot update on that bar nonetheless.
► This more accurate representation on historical bars of what will happen in the realtime bar is one of the two key reasons why using non-repainting data is preferable.
The other is that in realtime, your script will be using more reliable data and behave more consistently.
Misleading plots
Valiant attempts by coders to show non-repainting, higher timeframe data updating earlier than on our chart are futile. If updates occur one bar earlier because coders use the repainting version of the function, then so be it, but they must then also accept that their historical bars are not displaying information that is as accurate. Not informing script users of this is to mislead them. Coders should also be aware that if they choose to use repainting data in realtime, they are sacrificing reliability to speed and may be running a strategy that behaves very differently from the one they backtested, thus invalidating their tests.
When, however, coders make what are supposed to be non-repainting plots plot artificially early on historical bars, as in examples "c4" and "c5" of our script, they would want us to believe they have achieved the miracle of time travel. Our understanding of the current state of science dictates that for now, this is impossible. Using such techniques in scripts is plainly misleading, and public scripts using them will be moderated. We are coding trading tools here—not video games. Elementary ethics prescribe that we should not mislead traders, even if it means not being able to show sexy plots. As the great Feynman said: You should not fool the layman when you're talking as a scientist.
You can readily appreciate the fantasy plot of "c4", the thinnest line in black, by comparing its supposedly non-repainting behavior between historical bars and realtime bars. After updating—by miracle—as early as the wide yellow line that is repainting, it suddenly moves in a more realistic place when the script is running in realtime, in synch with our non-repainting lines. The "c5" version does not plot on the chart, but it displays in the Data Window. It is even worse than "c4" in that it also updates magically early on historical bars, but goes on to evaluate like the repainting yellow line in realtime, except one bar late.
Data Window
The Data Window shows the values of the chart's plots, then the values of both the inside and outside offsets used in our calculations, so you can see them change bar by bar. Notice their differences between historical and elapsed realtime bars, and the realtime bar itself. If you do not know about the Data Window, have a look at this essential tool for Pine coders in the Pine User Manual's page on Debugging . The conditional expressions used to calculate the offsets may seem tortuous but their objective is quite simple. When repainting is on, we use this form, so with no offset on all bars:
security(ticker, i_timeframe, i_source )
// which is equivalent to:
security(ticker, i_timeframe, i_source)
When repainting is off, we use two different and inverted offsets on historical bars and the realtime bar:
// Historical bars:
security(ticker, i_timeframe, i_source )
// Realtime bar (and thus, elapsed realtime bars):
security(ticker, i_timeframe, i_source )
The offsets in the first line show how we prevent repainting on historical bars without the need for the `lookahead` parameter. We use the value of the function call on the chart's previous bar. Since values between the repainting and non-repainting versions only differ on the timeframe's last bar, we can use the previous value so that the update only occurs on the timeframe's first bar, as it will in realtime when not repainting.
In the realtime bar, we use the second call, where the offsets are inverted. This is because if we used the first call in realtime, we would be fetching the value of the repainting function on the previous bar, so the close of the last bar. What we want, instead, is the data from the previous, higher timeframe bar , which has elapsed and is confirmed, and thus will not change throughout realtime bars, except on the first constituent chart bar belonging to a new higher timeframe.
After the offsets, the Data Window shows values for the `barstate.*` variables we use in our calculations.
█ NOTES
Why are we revisiting security() ?
For four reasons:
1 — We were seeing coders misuse our `f_secureSecurity()` function presented in How to avoid repainting when using security() .
Some novice coders were modifying the offset used with the history-referencing operator in the function, making it zero instead of one,
which to our horror, caused look-ahead bias when used with `lookahead = barmerge.lookahead_on`.
We wanted to present a safer function which avoids introducing the dreaded "lookahead" in the scripts of unsuspecting coders.
2 — The popularity of security() in screener-type scripts where coders need to use the full 40 calls allowed per script made us want to propose
a solid method of allowing coders to offer a repainting/no-repainting choice to their script users with only one security() call.
3 — We wanted to explain why some alternatives we see circulating are inadequate and produce misleading behavior.
4 — Our previous publication on security() focused on how to avoid repainting, yet many other considerations worthy of attention are not related to repainting.
Handling tuples
When sending function calls that return tuples with security() , our `f_security()` function will not work because Pine does not allow us to use the history-referencing operator with tuple return values. The solution is to integrate the inside offset to your function's arguments, use it to offset the results the function is returning, and then add the outside offset in a reassignment of the tuple variables, after security() returns its values to the script, as we do in our "c2" example.
Does it repaint?
We're pretty sure Wilder was not asked very often if RSI repainted. Why? Because it wasn't in fashion—and largely unnecessary—to ask that sort of question in the 80's. Many traders back then used daily charts only, and indicator values were calculated at the day's close, so everybody knew what they were getting. Additionally, indicator values were calculated by generally reputable outfits or traders themselves, so data was pretty reliable. Today, almost anybody can write a simple indicator, and the programming languages used to write them are complex enough for some coders lacking the caution, know-how or ethics of the best professional coders, to get in over their heads and produce code that does not work the way they think it does.
As we hope to have clearly demonstrated, traders do have legitimate cause to ask if MTF scripts repaint or not when authors do not specify it in their script's description.
► We recommend that authors always use our `f_security()` with `false` as the last argument to avoid repainting when fetching data dependent on OHLCV information. This is the only way to obtain reliable HTF data. If you want to offer users a choice, make non-repainting mode the default, so that if users choose repainting, it will be their responsibility. Non-repainting security() calls are also the only way for scripts to show historical behavior that matches the script's realtime behavior, so you are not misleading traders. Additionally, non-repainting HTF data is the only way that non-repainting alerts can be configured on MTF scripts, as users of MTF scripts cannot prevent their alerts from repainting by simply configuring them to trigger on the bar's close.
Data feeds
A chart at one timeframe is made up of multiple feeds that mesh seamlessly to form one chart. Historical bars can use one feed, and the realtime bar another, which brokers/exchanges can sometimes update retroactively so that elapsed realtime bars will reappear with very slight modifications when the browser's tab is refreshed. Intraday and daily chart prices also very often originate from different feeds supplied by brokers/exchanges. That is why security() calls at higher timeframes may be using a completely different feed than the chart, and explains why the daily high value, for example, can vary between timeframes. Volume information can also vary considerably between intraday and daily feeds in markets like stocks, because more volume information becomes available at the end of day. It is thus expected behavior—and not a bug—to see data variations between timeframes.
Another point to keep in mind concerning feeds it that when you are using a repainting security() plot in realtime, you will sometimes see discrepancies between its plot and the realtime bars. An artefact revealing these inconsistencies can be seen when security() plots sometimes skip a realtime chart bar during periods of high market activity. This occurs because of races between the chart and the security() feeds, which are being monitored by independent, concurrent processes. A blue arrow on the chart indicates such an occurrence. This is another cause of repainting, where realtime bar-building logic can produce different outcomes on one closing price. It is also another argument supporting our recommendation to use non-repainting data.
Alternatives
There is an alternative to using security() in some conditions. If all you need are OHLC prices of a higher timeframe, you can use a technique like the one Duyck demonstrates in his security free MTF example - JD script. It has the great advantage of displaying actual repainting values on historical bars, which mimic the code's behavior in the realtime bar—or at least on elapsed realtime bars, contrary to a repainting security() plot. It has the disadvantage of using the current chart's TF data feed prices, whereas higher timeframe data feeds may contain different and more reliable prices when they are compiled at the end of the day. In its current state, it also does not allow for a repainting/no-repainting choice.
When `lookahead` is useful
When retrieving non-price data, or in special cases, for experiments, it can be useful to use `lookahead`. One example is our Backtesting on Non-Standard Charts: Caution! script where we are fetching prices of standard chart bars from non-standard charts.
Warning users
Normal use of security() dictates that it only be used at timeframes equal to or higher than the chart's. To prevent users from inadvertently using your script in contexts where it will not produce expected behavior, it is good practice to warn them when their chart is on a higher timeframe than the one in the script's "Timeframe" field. Our `f_tfReminderAndErrorCheck()` function in this script does that. It can also print a reminder of the higher timeframe. It uses one security() call.
Intrabar timeframes
security() is not supported by TradingView when used with timeframes lower than the chart's. While it is still possible to use security() at intrabar timeframes, it then behaves differently. If no care is taken to send a function specifically written to handle the successive intrabars, security() will return the value of the last intrabar in the chart's timeframe, so the last 1H bar in the current 1D bar, if called at "60" from a "D" chart timeframe. If you are an advanced coder, see our FAQ entry on the techniques involved in processing intrabar timeframes. Using intrabar timeframes comes with important limitations, which you must understand and explain to traders if you choose to make scripts using the technique available to others. Special care should also be taken to thoroughly test this type of script. Novice coders should refrain from getting involved in this.
█ TERMINOLOGY
Timeframe
Timeframe , interval and resolution are all being used to name the concept of timeframe. We have, in the past, used "timeframe" and "resolution" more or less interchangeably. Recently, members from the Pine and PineCoders team have decided to settle on "timeframe", so from hereon we will be sticking to that term.
Multi-timeframe (MTF)
Some coders use "multi-timeframe" or "MTF" to name what are in fact "multi-period" calculations, as when they use MAs of progressively longer periods. We consider that a misleading use of "multi-timeframe", which should be reserved for code using calculations actually made from another timeframe's context and using security() , safe for scripts like Duyck's one mentioned earlier, or TradingView's Relative Volume at Time , which use a user-selected timeframe as an anchor to reset calculations. Calculations made at the chart's timeframe by varying the period of MAs or other rolling window calculations should be called "multi-period", and "MTF-anchored" could be used for scripts that reset calculations on timeframe boundaries.
Colophon
Our script was written using the PineCoders Coding Conventions for Pine .
The description was formatted using the techniques explained in the How We Write and Format Script Descriptions PineCoders publication.
Snippets were lifted from our MTF Selection Framework , then massaged to create the `f_tfReminderAndErrorCheck()` function.
█ THANKS
Thanks to apozdnyakov for his help with the innards of security() .
Thanks to bmistiaen for proofreading our description.
Look first. Then leap.
