TSI w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "Trend Strength Index" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█ Introduction and How it is Different
The "TSI with SuperTrend Decision - Strategy" combines the Trend Strength Index (TSI) with SuperTrend indicators to determine entry and exit points. Unlike traditional strategies that rely solely on one indicator, this method leverages the strengths of both TSI and SuperTrend to provide a more nuanced and adaptive trading strategy.
This dual approach allows for capturing trends more effectively, especially in volatile markets.
BTCUSD 8h LS Performance
█ Strategy, How it Works: Detailed Explanation
🔶 Trend Strength Index (TSI)
The TSI is a momentum oscillator that shows both the direction and strength of a trend. It is calculated by comparing the price movement with the bar index over a specified period. The formula for TSI is as follows:
```
TSI = (PC / |PC|)
where:
PC = Change in price over the period
```
In this strategy, TSI is calculated using the closing prices and a default period of 64 bars. The TSI values help identify overbought and oversold conditions, providing signals for potential market reversals.
🔶 SuperTrend Indicator
The SuperTrend is a trend-following indicator based on the average true range (ATR). It helps in identifying the direction of the market trend. The SuperTrend calculation involves:
```
SuperTrend = HLC3 ± (Factor * ATR)
where:
HLC3 = (High + Low + Close) / 3
Factor = User-defined multiplier
ATR = Average True Range over a period
```
The SuperTrend settings in this strategy include a length of 10 bars and a factor of 3.0.
Last Bull Cycle of BTC
🔶 Entry and Exit Conditions
The strategy uses the TSI and SuperTrend together to determine entry and exit points:
- Long Entry: When the SuperTrend indicates a downward trend (st.d < 0) and the TSI is above the oversold level (-0.241).
- Long Exit: When the SuperTrend indicates an upward trend (st.d > 0) and the TSI is below the overbought level (0.241).
- Short Entry: When the SuperTrend indicates an upward trend (st.d > 0) and the TSI is below the overbought level (0.241).
- Short Exit: When the SuperTrend indicates a downward trend (st.d < 0) and the TSI is above the oversold level (-0.241).
█ Trade Direction
The strategy allows users to select the trade direction through the `tradeDirection` input. The options are:
- Both: Enables both long and short trades.
- Long: Enables only long trades.
- Short: Enables only short trades.
█ Default Settings
- TSI Length: 64
- SuperTrend Length: 10
- SuperTrend Factor: 3.0
- Trade Direction: Both
- Take Profit (%): 30.0
- Stop Loss (%): 20.0
Impact of Default Settings
- TSI Length: A longer TSI period smooths out noise but may lag in identifying trends. A shorter period is more responsive but can generate false signals.
- SuperTrend Length: A shorter length provides quicker signals but can be prone to whipsaws. A longer length is more reliable but may delay entries and exits.
- SuperTrend Factor: A higher factor increases the distance of the SuperTrend from the price, reducing sensitivity to minor price fluctuations.
- Trade Direction: Allows flexibility in trading strategies by enabling both long and short trades based on market conditions.
- Take Profit and Stop Loss: These settings manage risk by automatically closing trades at predefined profit or loss levels. Higher percentages provide larger potential gains but also higher risk.
Cari dalam skrip untuk "range"
CE_ZLSMA_5MIN_CANDLECHART-- Overview
The "CE_ZLSMA_5MIN_CANDLECHART" strategy, developed by DailyPanda, is a comprehensive trading strategy designed for analyzing trading on 5-minute candlestick charts.
It aims to use some indicators calculated from a Hekin Ashi chart, while running it on a normal candlestick chart, making sure that no price distortion affects the strategy results .
It also brings a feature to show, on the candlestick chart, where the entries would take place on the HA chart, to also be able to study the effect that the price distortion would make on your backtest.
-- Credit
The code in this script is based on open-source indicators originally written by veryfid and everget, I've made significant changes and additions to the scripts but all credit for the idea goes to them, I just built on top of it:
-- Key Features
It incorporate already built indicators (ZLSMA) and CandelierExit (CE)
-- Zero Lag Least Squares Moving Average (ZLSMA) - by veryfid
The ZLSMA is used to detect trends with minimal lag, improving the accuracy of entry and exit signals.
It incorporates a double-smoothed linear regression to minimize lag and enhance trend-following capabilities.
Buy signals are generated when the price closes above the ZLSMA together with the CE signal.
It is calculated based on the HA candlestick pattern.
-- Chandelier Exit (CE) - by everget
The Chandelier Exit indicator is used to dynamically manage stop-loss levels based on the Average True Range (ATR).
It ensures that stop-loss levels are adaptive to market volatility, protecting profits and limiting losses.
The ATR period and multiplier can be customized to fit different trading styles and risk tolerances.
It is calculated based on the HA candlestick pattern.
-- Heikin Ashi Candles
The strategy leverages Heikin Ashi candlesticks to be able identify trends more clearly and leverage this to stay on winning trades longer.
Traders can choose to display Heikin Ashi candlesticks and order fills on the chart for better visualization.
-- Risk Management
The strategy includes multiple risk management options to protect traders' capital.
Maximum intraday loss limit based on a percentage of equity.
Maximum stop-loss in points to filter out entries with excessive risk.
Daily profit target to stop trading once the goal is achieved.
Options to use fixed contract sizes or dynamically adjust based on a percentage of equity.
These features help traders manage risk and ensure sustainable trading practices.
Moving Averages
Several moving averages (EMA 9, EMA 20, EMA 50, EMA 72, EMA 200, SMA 200, and SMA 500) are plotted to provide additional context and trend confirmation.
A "Zone of Value" is highlighted between the EMA 200 and SMA 200 to identify potential support and resistance areas.
-- Customizable Inputs
The strategy includes various customizable inputs, allowing traders to tailor it to their specific needs.
Start and stop trading times.
Risk management parameters (e.g., maximum stop-loss, daily drawdown limit, and daily profit target).
Display options for Heikin Ashi candles and moving averages.
ZLSMA length and offset.
-- Usage
-- Setting Up the Strategy
Configure the start year for the strategy and the trading hours using the input fields. The first candle of each day will be filled black for easy identification, while candles that are outside the allowed time range will be filled purple.
Customize the risk management parameters to match your risk tolerance and trading style.
Enable or disable the display of Heikin Ashi candlesticks and moving averages as desired.
-- Interpreting Signals
Buy signals are indicated by a "Buy" label when the Heikin Ashi close price is above the ZLSMA and the Chandelier Exit indicates a long position.
The strategy will automatically enter a long position with a stop-loss level determined the swing low.
Positions are closed when the close price falls below the ZLSMA.
-- Risk Management
The strategy monitors the maximum intraday loss and stops trading if the loss limit is reached.
If enabled, also stops trading once the daily profit target is achieved, helping to lock in gains.
You have the option to filter operations based on a maximum accepted stop-loss level, based on your risk tolerance.
You can also operate with a fixed amount of contracts or dynamically adjust it based on your allowed risk per trade, ensuring optimal protection of capital.
-- Visual Aids
The strategy plots various moving averages to provide additional trend context.
The "Zone of Value" between the EMA 200 and SMA 200 highlights potential support and resistance areas.
Heikin Ashi candlesticks and order fills can be displayed to enhance the difference this strategy would take if you were to backtest it on a Heikin Ashi chart.
-- Table of results
This strategy also breaks down the results on a monthly basis for better understanding of your capital development along the way.
-- Conclusion
The "CE_ZLSMA_5MIN_CANDLECHART" strategy is a tool for intraday traders looking to understand and leaverage the Heikin Ashi chart while still using the normal candle chart. Traders can customize the strategy to fit their specific needs, making it a versatile addition to any trading toolkit.
Universal Algo [Coff3eG]Universal Algo By G
Overview:
Universal Algo By G is a comprehensive LONG-ONLY trading strategy specifically designed for medium to long-term use in cryptocurrency markets, particularly Bitcoin. This algorithm can be manually adjusted to fit the volatility of specific coins, ensuring the best possible results. While it does not generate a large number of trades due to the nature of bull and bear market cycles, it has been rigorously backtested and forward-tested to ensure the strategy is not overfitted.
Core Features:
Integrated Systems: Universal Algo is built around five core systems, each contributing unique analytical perspectives to enhance trade signal reliability. These systems are designed to identify clear trend opportunities for significant gains while also employing logic to navigate through ranging markets effectively.
Optional Ranging Market Filter: Helps filter out noise, potentially enhancing signal clarity.
Market State Detection: Identifies four distinct market states:
Trending
Ranging
Danger (Possible top)
Possible Bottom
Global Liquidity Indicator (GLI) Integration: Leverages GLI values to identify positive liquidity trends.
Volatility Bands: Provides insights into market volatility.
Top and Bottom Detection: Shows possible bottoms with green backgrounds and red backgrounds for possible top detection.
The Market State Detection, GLI, Volatility Bands, and Top and Bottom Detection feature all serve as an expectation management feature.
Additional Features:
Optional Metrics Table: Displays strategy metrics and statistics, providing detailed insights into performance.
Customization Options: The script offers a range of user inputs, allowing for customization of the backtesting starting date, the decision to display the strategy equity curve, among other settings. These inputs cater to diverse trading needs and preferences, offering users control over their strategy implementation.
Operational Parameters:
Customizable Inputs: Users can adjust thresholds to match the coin's volatility, enhancing strategy performance.
Transparency and Logic Insight: While specific calculation details and proprietary indicators are integral to maintaining the uniqueness of Universal Algo, the strategy is grounded on well-established financial analysis techniques. These include momentum analysis, volatility assessments, and adaptive thresholding, among others, to formulate its trade signals. Notably, no single indicator is used in isolation; each indicator is combined with another to enhance signal accuracy and robustness. Some of the indicators include customized versions of the TEMA, Supertrend, Augmented Dickey-Fuller (ADF), and Weekly Positive Directional Movement Index (WPDM), all integrated together to create a cohesive and effective trading strategy.
System Operation:
Universal Algo works by taking the average score of the five core systems used for the signals. Three of these systems have been lengthened out to function as longer-term systems, while the remaining two operate at a slightly faster speed. This combination and averaging of systems help to balance the overall strategy, ensuring it maintains the right amount of speed to remain effective for medium to long-term use with minimal noise. The average score is then compared against customizable thresholds. The strategy will go long if the average score is above the threshold and short if it is below the threshold. This averaging mechanism helps to smooth out individual system anomalies and provides a more robust signal for trading decisions.
Originality and Usefulness:
Universal Algo is an original strategy that combines multiple proprietary and customized indicators to deliver robust trading signals. The strategy integrates various advanced indicators and methodologies, including:
System Indicator: Calculates a cumulative score based on recent price movements, aiding in trend detection.
Median For Loop: Utilizes percentile rank calculations of price data to gauge market direction.
Volatility Stop: A modified volatility-based stop-loss indicator that adjusts based on market conditions.
Supertrend: A customized supertrend indicator that uses percentile ranks and ATR for trend detection.
RSI and DEMA: Combines a modified RSI and DEMA for overbought/oversold conditions.
TEMA: Uses 3 different types of MA for trend detection and standard deviation bands for additional confirmation.
Detailed Explanation of Components and Their Interaction:
RSI (Relative Strength Index): Used to identify overbought and oversold conditions. In Universal Algo, RSI is combined with DEMA (Double Exponential Moving Average) to smooth the price data and provide clearer signals.
ATR (Average True Range): Used to measure market volatility. ATR is incorporated into the Volatility Stop and Supertrend indicators to adjust stop-loss levels and trend detection based on current market conditions.
DEMA (Double Exponential Moving Average): Provides a smoother price trend compared to traditional moving averages, reducing lag and making it easier to identify trend changes.
Modified TEMA (Triple Exponential Moving Average): Similar to DEMA but provides even greater smoothing, reducing lag further and enhancing trend detection accuracy.
Volatility Stop: Utilizes ATR to dynamically set stop-loss levels that adapt to changing market volatility. This helps in protecting profits and minimizing losses.
Customized Supertrend: Uses ATR and percentile ranks to determine trend direction and strength. This indicator helps in capturing major trends while filtering out market noise.
Median For Loop: Calculates percentile ranks of price data over a specified period to assess market direction. This helps in identifying potential reversals and trend continuations.
HMA (Hull Moving Average): A fast-acting moving average that reduces lag while maintaining smoothness. It helps in quickly identifying trend changes.
SMA (Simple Moving Average): A traditional moving average that provides baseline trend information. Combined with HMA and other indicators, it forms a comprehensive trend detection system.
Universal Algo offers a sophisticated blend of advanced indicators and proprietary logic that is not available in free or open-source scripts. Here are some reasons why it is worth paying for:
Customization and Flexibility: The strategy provides a high degree of customization, allowing users to adjust various parameters to suit their trading style and market conditions. This flexibility is often not available in free scripts.
Proprietary Indicators: The use of proprietary and customized indicators such as the TEMA, Supertrend, ADF, and WPDM ensures that the strategy is unique and not replicable by free or open-source scripts.
Integrated Systems: The strategy combines multiple systems and indicators to provide a more comprehensive and reliable trading signal. This integration helps to smooth out anomalies and reduces noise, providing clearer trading opportunities.
Rigorous Testing: Universal Algo has undergone extensive backtesting and forward-testing to ensure its robustness and reliability. The results demonstrate its ability to perform well under various market conditions, offering users confidence in its effectiveness.
Detailed Metrics and Analysis: The optional metrics table provides users with detailed insights into the strategy's performance, including metrics like equity, drawdown, Sharpe ratio, and more. This level of detail helps traders make informed decisions.
Value Addition: By providing a strategy that combines advanced indicators, customization options, and thorough testing, Universal Algo adds significant value to traders looking for a reliable and adaptable trading tool.
Realistic Trading Conditions:
Backtesting and Forward-Testing: Rigorous testing ensures performance and reliability, with a focus on prudent risk management. Default properties include an initial capital of $1000, 0 pyramiding, 20 slippage, 0.05% commission, and using 5% of equity for trades.
The strategy is designed and tested with a focus on achieving a balance between risk and reward, striving for robustness and reliability rather than unrealistic profitability promises. Realistic trading conditions are considered, including appropriate account size, commission, slippage, and sustainable risk levels per trade.
Concluding Thoughts:
Universal Algo By G is offered to the TradingView community as a robust tool for enhancing market analysis and trading strategies. It is designed with a commitment to quality, innovation, and adaptability, aiming to provide valuable insights and decision support across various market conditions. Potential users are encouraged to evaluate Universal Algo within the context of their overall trading approach and objectives.
RunRox - Backtesting System (ASMC)Introducing RunRox - Backtesting System (ASMC), a specially designed backtesting system built on the robust structure of our Advanced SMC indicator. This innovative tool evaluates various Smart Money Concept (SMC) trading setups and serves as an automatic optimizer, displaying which entry and exit points have historically shown the best results. With cutting-edge technology, RunRox - Backtesting System (ASMC) provides you with effective strategies, maximizing your trading potential and taking your trading to the next level
🟠 HOW OUR BACKTESTING SYSTEM WORKS
Our backtesting system for the Advanced SMC (ASMC) indicator is meticulously designed to provide traders with a thorough analysis of their Smart Money Concept (SMC) strategies. Here’s an overview of how it works:
🔸 Advanced SMC Structure
Our ASMC indicator is built upon an enhanced SMC structure that integrates the Institutional Distribution Model (IDM), precise retracements, and five types of order blocks (CHoCH OB, IDM OB, Local OB, BOS OB, Extreme OB). These components allow for a detailed understanding of market dynamics and the identification of key trading opportunities.
🔸 Data Integration and Analysis
1. Historical Data Testing:
Our system tests various entry and exit points using historical market data.
The ASMC indicator is used to simulate trades based on predefined SMC setups, evaluating their effectiveness over a specified time period.
Traders can select different parameters such as entry points, stop-loss, and take-profit levels to see how these setups would have performed historically.
2. Entry and Exit Events:
The backtester can simulate trades based on 12 different entry events, 14 target events, and 14 stop-loss events, providing a comprehensive testing framework.
It allows for testing with multiple combinations of entry and exit strategies, ensuring a robust evaluation of trading setups.
3. Order Block Sensitivity:
The system uses the sensitivity settings from the ASMC indicator to determine the most relevant order blocks and fair value gaps (FVGs) for entry and exit points.
It distinguishes between different types of order blocks, helping traders identify strong institutional zones versus local zones.
🔸 Optimization Capabilities
1. Auto-Optimizer:
The backtester includes an auto-optimizer feature that evaluates various setups to find those with the best historical performance.
It automatically adjusts parameters to identify the most effective strategies for both trend-following and counter-trend trading.
2. Stop Loss and Take Profit Optimization:
It optimizes stop-loss and take-profit levels by testing different settings and identifying those that provided the best historical results.
This helps traders refine their risk management and maximize potential returns.
3. Trailing Stop Optimization:
The system also optimizes trailing stops, ensuring that traders can maximize their profits by adjusting their stops dynamically as the market moves.
🔸 Comprehensive Reporting
1. Performance Metrics:
The backtesting system provides detailed reports, including key performance metrics such as Net Profit, Win Rate, Profit Factor, and Max Drawdown.
These metrics help traders understand the historical performance of their strategies and make data-driven decisions.
2. Flexible Settings:
Traders can adjust initial balance, commission rates, and risk per trade settings to simulate real-world trading conditions.
The system supports testing with different leverage settings, allowing for realistic assessments even with tight stop-loss levels.
🔸 Conclusion
The RunRox Backtesting System (ASMC) is a powerful tool for traders seeking to validate and optimize their SMC strategies. By leveraging historical data and sophisticated optimization algorithms, it provides insights into the most effective setups, enhancing trading performance and decision-making.
🟠 HERE ARE THE AVAILABLE FEATURES
Historical backtesting for any setup – Select any entry point, exit point, and various stop-loss options to see the results of your setup on historical data.
Auto-optimizer for finding the best setups – The indicator displays settings that have shown the best results historically, providing valuable insights.
Auto-optimizer for counter-trend setups – Discover entry and exit points for counter-trend trading based on historical performance.
Auto-optimizer for stop-loss – The indicator shows stop-loss points that have been most effective historically.
Auto-optimizer for take-profit – The indicator identifies take-profit points that have performed well in historical trading data.
Auto-optimizer for trailing stop – The indicator presents trailing stop settings that have shown the best historical results.
And much more within our indicator, all of which we will cover in this post. Next, we will showcase the possible entry points, targets, and stop-loss options available for testing your strategies
🟠 ENTRY SETTINGS
12 Event Triggers for Trade Entry
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Trade Direction Options
Long Only: Enter long positions only
Short Only: Enter short positions only
Long and Short: Enter both long and short positions based on trend
3 Levels for Order Block/FVG Entries
Beginning: Enter the trade at the first touch of the Order Block/FVG
Middle: Enter the trade when the middle of the Order Block/FVG is reached
End: Enter the trade upon full filling of the Order Block/FVG
*Three levels work only for Order Blocks and FVG. For trade entries based on BOS or CHoCH, these settings do not apply as these parameters are not available for these types of entries
You can choose any combination of trade entries imaginable.
🟠 TARGET SETTINGS
14 Target Events, Including Fixed % and Fixed RR (Risk/Reward):
Fixed - % change in price
Fixed RR - Risk Reward per trade
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Levels of Order Block/FVG for Target
Beginning: Close the trade at the first touch of your target.
Middle: Close the trade at the midpoint of your chosen target.
End: Close the trade when your target is fully filled.
Customizable Parameters
Easily set your Fixed % and Fixed RR targets with a user-friendly input field. This field works only for the Fixed and Fixed RR entry parameters. When selecting a different entry point, this field is ignored
Choose any combination of target events to suit your trading strategy.
🟠 STOPLOSS SETTINGS
14 Possible StopLoss Events Including Entry Orderblock/FVG
Fixed - Fix the loss on the trade when the price moves by N%
Entry Block
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Levels for Order Blocks/FVG Exits
Beginning: Exit the trade at the first touch of the order block/FVG.
Middle: Exit the trade at the middle of the order block/FVG.
End: Exit the trade at the full completion of the order block/FVG.
Dedicated Field for Setting Fixed % Value
Set a fixed % value in a dedicated field for the Fixed parameter. This field works only for the Fixed parameter. When selecting other exit parameters, this field is ignored.
🟠 ADDITIONAL SETTINGS
Trailing Stop, %
Set a Trailing Stop as a percentage of your trade to potentially increase profit based on historical data.
Move SL to Breakeven, bars
Move your StopLoss to breakeven after exiting the entry zone for a specified number of bars. This can enhance your potential WinRate based on historical performance.
Skip trade if RR less than
This feature allows you to skip trades where the potential Risk-to-Reward ratio is less than the number set in this field.
🟠 EXAMPLE OF MANUAL SETUP
For example, let me show you how it works on the chart. You select entry parameters, stop loss parameters, and take profit parameters for your trades, and the strategy automatically tests this setup on historical data, allowing you to see the results of this strategy.
In the screenshot above, the parameters were as follows:
Trade Entry: CHoCH OB (Beginning)
Stop Loss: Entry Block
Take Profit: Break of BOS
The indicator will automatically test all possible trades on the chart and display the results for this setup.
🟠 AUTO OPTIMIZATION SETTINGS
In the screenshot above, you can see the optimization table displaying various entry points, exits, and stop-loss settings, along with their historical performance results and other parameters. This feature allows you to identify trading setups that have shown the best historical outcomes.
This functionality will enhance your trading approach, providing you with valuable insights based on historical data. You’ll be aware of the Smart Money Concept settings that have historically worked best for any specific chart and timeframe.
Our indicator includes various optimization options designed to help you find the most effective settings based on historical data. There are 5 optimization modes, each offering unique benefits for every trader
Trend Entry - Optimization of the best settings for trend-following trades. The strategy will enter trades only in the direction of the trend. If the trend is upward, it will look for long entry points and vice versa.
Counter Trend Entry - Finding setups against the trend. If the trend is upward, the script will search for short entry points. This is the opposite of trend entry optimization.
Stop Loss - Identifying stop-loss points that showed the best historical performance for the specific setup you have configured. This helps in finding effective exit points to minimize losses.
Take Profit - Determining targets for the configured setup based on historical performance, helping to identify potentially profitable take profit levels.
Trailing Stop - Finding optimal percentages for the trailing stop function based on historical data, which can potentially increase the profit of your trades.
Ability to set parameters for auto-optimization within a specified range. For example, if you choose FixRR TP from 1 to 10, the indicator will automatically test all possible Risk Reward Take Profit variations from 1 to 10 and display the results for each parameter individually.
Ability to set initial deposit parameters, position commissions, and risk per trade as a fixed percentage or fixed amount. Additionally, you can set the maximum leverage for a trade.
There are times when the stop loss is very close to the entry point, and adhering to the risk per trade values set in the settings may not allow for such a loss in any situation. That’s why we added the ability to set the maximum possible leverage, allowing you to test your trading strategy even with very tight stop losses.
Duplicated Smart Money Structure settings from our Advanced SMC indicator that you can adjust to match your trading style flexibly. All these settings will be taken into account during the optimization process or when manually calculating settings.
Additionally, you can test your strategy based on higher timeframe order blocks. For example, you can test a strategy on a 1-minute chart while displaying order blocks from a 15-minute timeframe. The auto-optimizer will consider all these parameters, including higher timeframe order blocks, and will enter trades based on these order blocks.
Highly flexible dashboard and results optimization settings allow you to display the tables you need and sort results by six different criteria: Profit Factor, Profit, Winrate, Max Drawdown, Wins, and Trades. This enables you to find the exact setup you desire, based on these comprehensive data points.
🟠 ALERT CUSTOMIZATION
With this indicator, you can set up buy and sell alerts based on the test results, allowing you to create a comprehensive trading strategy. This feature enables you to receive real-time signals, making it a powerful tool for implementing your trading strategies.
🟠 STRATEGY PROPERTIES
For backtesting, we used realistic initial data for entering trades, such as:
Starting balance: $1000
Commission: 0.01%
Risk per trade: 1%
To ensure realistic data, we used the above settings. We offer two methods for calculating your order size, and in our case, we used a 1% risk per trade. Here’s what it means:
Risk per trade: This is the maximum loss from your deposit if the trade goes against you. The trade volume can change depending on your stop-loss distance from the entry point. Here’s the formula we use to calculate the possible volume for a single trade:
1. quantity = percentage_risk * balance / loss_per_1_contract (incl. fee)
Then, we calculate the maximum allowed volume based on the specified maximum leverage:
2. max_quantity = maxLeverage * balance / entry_price
3. If quantity < max_quantity, meaning the leverage is less than the maximum allowed, we keep quantity. If quantity > max_quantity, we use max_quantity (the maximum allowed volume according to the set leverage).
This way, depending on the stop-loss distance, the position size can vary and be up to 100% of your deposit, but the loss in each trade will not exceed the set percentage, which in our case is 1% for this backtest. This is a standard risk calculation method based on your stop-loss distance.
🔸 Statistical Significance of Trade Data
In our strategy, you may notice there weren’t enough trades to form statistically significant data. This is inherent to the Smart Money Concept (SMC) strategy, where the focus is not on the number of trades but rather on the risk-to-reward ratio per trade. In SMC strategies, it’s crucial to avoid taking numerous uncertain setups and instead perform a comprehensive analysis of the market situation.
Therefore, our strategy results show fewer than 100 trades. It’s important to understand that this small sample size isn’t statistically significant and shouldn’t be relied upon for strategy analysis. Backtesting with a small number of trades should not be used to draw conclusions about the effectiveness of a strategy.
🔸 Versatile Use Cases
The methods of using this indicator are numerous, ranging from identifying potentially the best-performing order blocks on the chart to creating a comprehensive trading strategy based on the data provided by our indicator. We believe that every trader will find a valuable application for this tool, enhancing their entry and exit points in trades.
Disclaimer
Past performance is not indicative of future results. The results shown by this indicator do not guarantee similar outcomes in the future. Use this tool as part of a comprehensive trading strategy, considering all market conditions and risks.
How to access
For access to this indicator, please read the author’s instructions below this post
Strategic Multi-Step Supertrend - Strategy [presentTrading]The code is mainly developed for me to stimulate the multi-step taking profit function for strategies. The result shows the drawdown can be reduced but at the same time reduced the profit as well. It can be a heuristic for futures leverage traders.
█ Introduction and How it is Different
The "Strategic Multi-Step Supertrend" is a trading strategy designed to leverage the power of multiple steps to optimize trade entries and exits across the Supertrend indicator. Unlike traditional strategies that rely on single entry and exit points, this strategy employs a multi-step approach to take profit, allowing traders to lock in gains incrementally. Additionally, the strategy is adaptable to both long and short trades, providing a comprehensive solution for dynamic market conditions.
This template strategy lies in its dual Supertrend calculation, which enhances the accuracy of trend detection and provides more reliable signals for trade entries and exits. This approach minimizes false signals and increases the overall profitability of trades by ensuring that positions are entered and exited at optimal points.
BTC 6h L/S Performance
█ Strategy, How It Works: Detailed Explanation
The "Strategic Multi-Step Supertrend Trader" strategy utilizes two Supertrend indicators calculated with different parameters to determine the direction and strength of the market trend. This dual approach increases the robustness of the signals, reducing the likelihood of entering trades based on false signals. Here is a detailed breakdown of how the strategy operates:
🔶 Supertrend Indicator Calculation
The Supertrend indicator is a trend-following overlay on the price chart, typically used to identify the direction of the trend. It is calculated using the Average True Range (ATR) to ensure that the indicator adapts to market volatility. The formula for the Supertrend indicator is:
Upper Band = (High + Low) / 2 + (Factor * ATR)
Lower Band = (High + Low) / 2 - (Factor * ATR)
Where:
- High and Low are the highest and lowest prices of the period.
- Factor is a user-defined multiplier.
- ATR is the Average True Range over a specified period.
The Supertrend changes its direction based on the closing price in relation to these bands.
🔶 Entry-Exit Conditions
The strategy enters long positions when both Supertrend indicators signal an uptrend, and short positions when both indicate a downtrend. Specifically:
- Long Condition: Supertrend1 < 0 and Supertrend2 < 0
- Short Condition: Supertrend1 > 0 and Supertrend2 > 0
- Long Exit Condition: Supertrend1 > 0 and Supertrend2 > 0
- Short Exit Condition: Supertrend1 < 0 and Supertrend2 < 0
🔶 Multi-Step Take Profit Mechanism
The strategy features a multi-step take profit mechanism, which allows traders to lock in profits incrementally. This is achieved through four user-configurable take profit levels. For each level, the strategy specifies a percentage increase (for long trades) or decrease (for short trades) in the entry price at which a portion of the position is exited:
- Step 1: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent1 / 100)
- Step 2: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent2 / 100)
- Step 3: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent3 / 100)
- Step 4: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent4 / 100)
This staggered exit strategy helps in locking profits at multiple levels, thereby reducing risk and increasing the likelihood of capturing the maximum possible profit from a trend.
BTC Local
█ Trade Direction
The strategy is highly flexible, allowing users to specify the trade direction. There are three options available:
- Long Only: The strategy will only enter long trades.
- Short Only: The strategy will only enter short trades.
- Both: The strategy will enter both long and short trades based on the Supertrend signals.
This flexibility allows traders to adapt the strategy to various market conditions and their own trading preferences.
█ Usage
1. Add the strategy to your trading platform and apply it to the desired chart.
2. Configure the take profit settings under the "Take Profit Settings" group.
3. Set the trade direction under the "Trade Direction" group.
4. Adjust the Supertrend settings in the "Supertrend Settings" group to fine-tune the indicator calculations.
5. Monitor the chart for entry and exit signals as indicated by the strategy.
█ Default Settings
- Use Take Profit: True
- Take Profit Percentages: Step 1 - 6%, Step 2 - 12%, Step 3 - 18%, Step 4 - 50%
- Take Profit Amounts: Step 1 - 12%, Step 2 - 8%, Step 3 - 4%, Step 4 - 0%
- Number of Take Profit Steps: 3
- Trade Direction: Both
- Supertrend Settings: ATR Length 1 - 10, Factor 1 - 3.0, ATR Length 2 - 11, Factor 2 - 4.0
These settings provide a balanced starting point, which can be customized further based on individual trading preferences and market conditions.
Chande Kroll Trend Strategy (SPX, 1H) | PINEINDICATORSThe "Chande Kroll Stop Strategy" is designed to optimize trading on the SPX using a 1-hour timeframe. This strategy effectively combines the Chande Kroll Stop indicator with a Simple Moving Average (SMA) to create a robust method for identifying long entry and exit points. This detailed description will explain the components, rationale, and usage to ensure compliance with TradingView's guidelines and help traders understand the strategy's utility and application.
Objective
The primary goal of this strategy is to identify potential long trading opportunities in the SPX by leveraging volatility-adjusted stop levels and trend-following principles. It aims to capture upward price movements while managing risk through dynamically calculated stops.
Chande Kroll Stop Parameters:
Calculation Mode: Offers "Linear" and "Exponential" options for position size calculation. The default mode is "Exponential."
Risk Multiplier: An adjustable multiplier for risk management and position sizing, defaulting to 5.
ATR Period: Defines the period for calculating the Average True Range (ATR), with a default of 10.
ATR Multiplier: A multiplier applied to the ATR to set stop levels, defaulting to 3.
Stop Length: Period used to determine the highest high and lowest low for stop calculation, defaulting to 21.
SMA Length: Period for the Simple Moving Average, defaulting to 21.
Calculation Details:
ATR Calculation: ATR is calculated over the specified period to measure market volatility.
Chande Kroll Stop Calculation:
High Stop: The highest high over the stop length minus the ATR multiplied by the ATR multiplier.
Low Stop: The lowest low over the stop length plus the ATR multiplied by the ATR multiplier.
SMA Calculation: The 21-period SMA of the closing price is used as a trend filter.
Entry and Exit Conditions:
Long Entry: A long position is initiated when the closing price crosses over the low stop and is above the 21-period SMA. This condition ensures that the market is trending upward and that the entry is made in the direction of the prevailing trend.
Exit Long: The long position is exited when the closing price falls below the high stop, indicating potential downward movement and protecting against significant drawdowns.
Position Sizing:
The quantity of shares to trade is calculated based on the selected calculation mode (linear or exponential) and the risk multiplier. This ensures position size is adjusted dynamically based on current market conditions and user-defined risk tolerance.
Exponential Mode: Quantity is calculated using the formula: riskMultiplier / lowestClose * 1000 * strategy.equity / strategy.initial_capital.
Linear Mode: Quantity is calculated using the formula: riskMultiplier / lowestClose * 1000.
Execution:
When the long entry condition is met, the strategy triggers a buy signal, and a long position is entered with the calculated quantity. An alert is generated to notify the trader.
When the exit condition is met, the strategy closes the position and triggers a sell signal, accompanied by an alert.
Plotting:
Buy Signals: Indicated with an upward triangle below the bar.
Sell Signals: Indicated with a downward triangle above the bar.
Application
This strategy is particularly effective for trading the SPX on a 1-hour timeframe, capitalizing on price movements by adjusting stop levels dynamically based on market volatility and trend direction.
Default Setup
Initial Capital: $1,000
Risk Multiplier: 5
ATR Period: 10
ATR Multiplier: 3
Stop Length: 21
SMA Length: 21
Commission: 0.01
Slippage: 3 Ticks
Backtesting Results
Backtesting indicates that the "Chande Kroll Stop Strategy" performs optimally on the SPX when applied to the 1-hour timeframe. The strategy's dynamic adjustment of stop levels helps manage risk effectively while capturing significant upward price movements. Backtesting was conducted with a realistic initial capital of $1,000, and commissions and slippage were included to ensure the results are not misleading.
Risk Management
The strategy incorporates risk management through dynamically calculated stop levels based on the ATR and a user-defined risk multiplier. This approach ensures that position sizes are adjusted according to market volatility, helping to mitigate potential losses. Trades are sized to risk a sustainable amount of equity, adhering to the guideline of risking no more than 5-10% per trade.
Usage Notes
Customization: Users can adjust the ATR period, ATR multiplier, stop length, and SMA length to better suit their trading style and risk tolerance.
Alerts: The strategy includes alerts for buy and sell signals to keep traders informed of potential entry and exit points.
Pyramiding: Although possible, the strategy yields the best results without pyramiding.
Justification of Components
The Chande Kroll Stop indicator and the 21-period SMA are combined to provide a robust framework for identifying long trading opportunities in trending markets. Here is why they work well together:
Chande Kroll Stop Indicator: This indicator provides dynamic stop levels that adapt to market volatility, allowing traders to set logical stop-loss levels that account for current price movements. It is particularly useful in volatile markets where fixed stops can be easily hit by random price fluctuations. By using the ATR, the stop levels adjust based on recent market activity, ensuring they remain relevant in varying market conditions.
21-Period SMA: The 21-period SMA acts as a trend filter to ensure trades are taken in the direction of the prevailing market trend. By requiring the closing price to be above the SMA for long entries, the strategy aligns itself with the broader market trend, reducing the risk of entering trades against the overall market direction. This helps to avoid false signals and ensures that the trades are in line with the dominant market movement.
Combining these two components creates a balanced approach that captures trending price movements while protecting against significant drawdowns through adaptive stop levels. The Chande Kroll Stop ensures that the stops are placed at levels that reflect current volatility, while the SMA filter ensures that trades are only taken when the market is trending in the desired direction.
Concepts Underlying Calculations
ATR (Average True Range): Used to measure market volatility, which informs the stop levels.
SMA (Simple Moving Average): Used to filter trades, ensuring positions are taken in the direction of the trend.
Chande Kroll Stop: Combines high and low price levels with ATR to create dynamic stop levels that adapt to market conditions.
Risk Disclaimer
Trading involves substantial risk, and most day traders incur losses. The "Chande Kroll Stop Strategy" is provided for informational and educational purposes only. Past performance is not indicative of future results. Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and risk tolerance.
trend_switch
█ Description
Asset price data was time series data, commonly consisting of trends, seasonality, and noise. Many applicable indicators help traders to determine between trend or momentum to make a better trading decision based on their preferences. In some cases, there is little to no clear market direction, and price range. It feels much more appropriate to use a shorter trend identifier, until clearly defined market trend. The indicator/strategy developed with the notion aims to automatically switch between shorter and longer trend following indicator. There were many methods that can be applied and switched between, however in this indicator/strategy will be limited to the use of predictive moving average and MESA adaptive moving average (Ehlers), by first determining if there is a strong trend identified by calculating the slope, if slope value is between upper and lower threshold assumed there is not much price direction.
█ Formula
// predictive moving average
predict = (2*wma1-wma2)
trigger = (4*predict+3*predict +2*predict *predict)
// MESA adaptive moving average
mama = alpha*src+(1-alpha)*mama
fama = .5*alpha*mama+(1-.5-alpha)*fama
█ Feature
The indicator will have a specified default parameter of:
source = ohlc4
lookback period = 10
threshold = 10
fast limit = 0.5
slow limit = 0.05
Strategy type can be switched between Long/Short only and Long-Short strategy
Strategy backtest period
█ How it works
If slope between the upper (red) and lower (green) threshold line, assume there is little to no clear market direction, thus signal predictive moving average indicator
If slope is above the upper (red) or below the lower (green) threshold line, assume there is a clear trend forming, the signal generated from the MESA adaptive moving average indicator
█ Example 1 - Slope fall between the Threshold - activate shorter trend
█ Example 2 - Slope fall above/below Threshold - activate longer trend
IsAlgo - AI Trend Strategy► Overview:
The AI Trend Strategy employs a combination of technical indicators to guide trading decisions across various markets and timeframes. It uses a custom Super Trend indicator and an Exponential Moving Average (EMA) to analyze market trends and executes trades based on specific candlestick patterns. This strategy includes options for setting stop losses, take profit levels, and features an alert system for trade notifications.
► Description:
This strategy focuses on identifying the optimal "entry candle," which signals either a potential correction within the ongoing trend or the emergence of a new trend. The entry criteria for this candle are highly customizable, allowing traders to specify dimensions such as the candle's minimum and maximum size and body ratio. Additional settings include whether this candle should be the highest or lowest compared to recent candles and if a confirmation candle is necessary to validate the entry.
The Super Trend indicator is central to the strategy’s operation, dictating the direction of trades by identifying bullish or bearish trends. Traders have the option to configure trades to align with the direction of the trend identified by this indicator, or alternatively, to take positions counter to the trend for potential reversal strategies. This flexibility can be crucial during varying market conditions.
Additionally, the strategy incorporates an EMA alongside the Super Trend indicator to further analyze trend directions. This combined approach aims to reduce the occurrence of false signals and improve the strategy's overall trend analysis.
The learning algorithm is a standout feature of the AI Trend Strategy. After accumulating data from a predefined number of trades (e.g., after the first 100 trades), the algorithm begins to analyze past performances to identify patterns in wins and losses. It considers variables such as the distance from the current price to the trend line, the range between the highest and lowest prices during the trend, and the duration of the trend. This data informs the algorithm's predictions for future trades, aiming to improve accuracy and reduce losses by adapting to the evolving market conditions.
► Examples of Trade Execution:
1. In an Uptrend: The strategy might detect a suitable entry candle during a correction phase, which aligns with the continuing uptrend for a potential long trade.
2. In a Downtrend: Alternatively, the strategy might identify an entry candle at the end of a downtrend, suggesting a potential reversal or correction where a long trade could be initiated.
3. In an Uptrend: The strategy may also spot an entry candle at the end of an uptrend and execute a short trade, anticipating a reversal or significant pullback.
4. In a Downtrend: The strategy might find a suitable entry candle during a correction phase, indicating a continuation of the downtrend for a potential short trade.
These examples illustrate how the strategy identifies potential trading opportunities based on trend behavior and candlestick patterns.
► Features and Settings:
⚙︎ Trend: Utilizes a custom Super Trend indicator to identify the direction of the market trend. Users can configure the strategy to execute trades in alignment with this trend, take positions contrary to the trend, or completely ignore the trend information for their trading decisions.
⚙︎ Moving average: Employs an Exponential Moving Average (EMA) to further confirm the trend direction indicated by the Super Trend indicator. This setting can be used in conjunction with the Super Trend or disabled if preferred.
⚙︎ Entry candle: Defines the criteria for the candle that triggers a trade. Users can customize aspects such as the candle's size, body, and its relative position to previous candles to ensure it meets specific trading requirements before initiating a trade.
⚙︎ Learning algorithm: This component uses historical trade data to refine the strategy. It assesses various aspects of past trades, such as price trends and market conditions, to make more informed trading decisions in the future.
⚙︎ Trading session: Users can define specific trading hours during which the strategy should operate, allowing trades to be executed only during preferred market periods.
⚙︎ Trading days: This option enables users to specify which days the strategy should be active, providing the flexibility to avoid trading on certain days of the week if desired.
⚙︎ Backtesting: Enables a period during which the strategy can be tested over a selected start and end date, with an option to deactivate this feature if not needed.
⚙︎ Trades: Detailed configuration options include the direction of trades (long, short, or both), position sizing (fixed or percentage-based), the maximum number of open trades, and limitations on the number of trades per day or based on trend changes.
⚙︎ Trades Exit: Offers various strategies for exiting trades, such as setting limits on profits or losses, specifying the duration a trade should remain open, or closing trades based on trend reversal signals.
⚙︎ Stop loss: Various methods for setting stop losses are available, including fixed pips, based on Average True Range (ATR), or utilizing the highest or lowest price points within a designated number of previous candles. Another option allows for closing the trade after a specific number of candles moving in the opposite direction.
⚙︎ Break even: This feature adjusts the stop loss to a break-even point under certain conditions, such as reaching predefined profit levels, to protect gains.
⚙︎ Trailing stop: The trailing stop feature adjusts the stop loss as the trade moves into profit, aiming to secure gains while potentially capturing further upside.
⚙︎ Take profit: Up to three take profit levels can be established using various methods, such as a fixed amount of pips, risk-to-reward ratios based on the stop loss, ATR, or after a set number of candles that move in the direction of the trade.
⚙︎ Alerts: Includes a comprehensive alert system that informs the user of all significant actions taken by the strategy, such as trade openings and closings. It supports placeholders for dynamic values like take profit levels, stop loss prices, and more.
⚙︎ Dashboard: Provides a visual display of detailed information about ongoing and past trades on the chart, helping users monitor the strategy’s performance and make informed decisions.
► Backtesting Details:
Timeframe: 15-minute BTCUSD chart.
Initial Balance: $10,000.
Order Size: 4% of equity per trade.
Commission: 0.01%.
Slippage: 5 ticks.
Risk Management: Strategic stop loss settings are applied based on the most extreme price points within the last 18 candles.
Trend Crawler with Dynamic TP and Trailing Stop### Description of "Trend Crawler with Dynamic TP and Trailing Stop"
#### Overview
The "Trend Crawler with Dynamic TP and Trailing Stop" is a comprehensive trading strategy designed for medium-frequency trading on various timeframes and markets. It utilizes a combination of trend identification and volatility analysis to determine optimal entry and exit points, aiming to maximize profitability by adapting to changing market conditions.
#### Strategy Mechanics
1. **Moving Averages**: Users can select between Simple Moving Average (SMA) and Exponential Moving Average (EMA) to define the trend. The strategy uses two moving averages (fast and slow) to identify the trend direction. A crossover of the fast MA above the slow MA signals a potential bullish trend, while a crossunder signals a bearish trend.
2. **Volume Analysis**: The strategy incorporates volume analysis to confirm the strength of the trend. It calculates a standard deviation of volume from its moving average to detect significant increases in trading activity, which supports the trend direction indicated by the MAs.
3. **Price Spread and RSI**: It uses the price spread (difference between the close and open of each bar) and the Relative Strength Index (RSI) to filter entries based on market momentum and overbought/oversold conditions. This helps in refining the entries to avoid weak or overly extended moves.
4. **Dynamic Take Profit and Trailing Stop**:
- **Trailing Stop**: As the position moves into profit, the strategy adjusts the stop loss dynamically to protect gains, using a trailing stop mechanism.
- **Dynamic Take Profit**: The take profit levels are adjusted based on the volatility (measured by the standard deviation of the price spread) to capture maximum profit from significant moves.
#### Usage
To use the strategy:
- Set the desired moving average type and lengths according to the asset and timeframe being traded.
- Adjust the RSI thresholds to match the market's volatility and trading style.
- Set the base take profit and stop loss levels along with the trailing stop distance based on risk tolerance and trading objectives.
#### Justification for Originality
While the use of moving averages, RSI, and volume analysis may be common, the integration of these elements with dynamic adjustments for take profit and trailing stops based on real-time volatility analysis offers a unique approach. The strategy adapts not just to trend direction but also to the market's momentum and volatility, providing a tailored trading solution that goes beyond standard indicator-based strategies.
#### Strategy Results and Settings
Backtesting should be conducted with realistic account sizes and include considerations for commission and slippage to ensure that the results are not misleading. Risk per trade should be kept within a sustainable range (ideally less than 5% of account equity), and the strategy should be tested over a sufficient sample size (at least 100 trades) to validate its effectiveness.
#### Chart Presentation
The script’s output includes:
- Colored backgrounds to indicate bullish or bearish market conditions.
- Plots of trailing stops to visually manage risk.
- Entry points are marked with shapes on the chart, providing clear visual cues for trading decisions.
#### Conclusion
This strategy offers traders a robust framework for trend following with enhanced risk management through dynamic adjustments based on real-time market analysis. It's designed to be versatile and adaptable to a wide range of markets and trading styles, providing traders with a tool that not only follows trends but also adapts to market changes to secure profits and reduce losses.
Trend Catcher Strategywhat is Trend Catcher Strategy?
it is a strategy that opens long or short positions in the direction of the trend.
what it does?
TCS detects trend formations using its own unique method. Then, it opens a position in the direction of the trend and closes a part of the opened transaction (half according to default values) when the price reaches a certain level, and moves the remaining position to the point where it thinks the trend is over. You can easily understand how it works by looking at the images:
how it does it?
It obtains a value called a "limit" by dividing the difference between the highest value and the lowest value in a certain range (that is, the vector sum) to the sum of the lengths of the candles in a certain range (the total distance traveled). then multiplies this by 100 to get a percentage value. The closer this value is to 100, the stronger the trend.
Spot Martingale KuCoin - The Quant ScienceINTRODUCTION
Backtesting software of the Spot Martingale algorithm offered by the KuCoin exchange.
This script replicates the logic used by the KuCoin bot and is useful for analyzing strategy on any cryptocurrency historical series.
It's not intended as an automatic trading algorithm and does not offer the possibility of automatic order execution.
The trader will use this software exclusively to research the best parameters with which to work on KuCoin.
LOGIC OF EXECUTION
The execution of orders is composed as follows:
1) Start Martingale: initial order
2) Martingale-Number: orders following Start Martingale
(A) The software is designed and developed to replicate trading without taking into account technical indicators or particular market conditions. The Initial Order (Start Martingale) will be executed immediately the close of the previous Martingale when the balance of market orders is zero. It will use the capital set in the Properties section for the initial order.
(B) After the first order, the software will open new orders as the price decreases. For orders following Start Martingale, the initial capital, multiplier, and number of orders in the exponential growth context are considered. The multiplier is the factor that determines the proportional increase in capital with each new order. The number of orders, indicates how many times the multiplier is applied to increase the investment.
Example
To find out the capital used in Martingale order number 5, with a Multiple For Position Increase equal to 2 and a starting capital of $100, the formula will be as follows:
Martingale Order = ($100 * (2 * 2 * 2 * 2 * 2)) = $100 * 32 = $3.200
(C) A multiplier is used for each new order that will increase the quantity purchased.
(D) All previously open orders are closed once the take profit is reached.
USER MANUAL
The user interface consists of two main sections:
1. Settings
Percentage Drop for Position Increase (0.1-15%) : percentage distance between Martingale orders. For example, if you set 5% each new order will be opened after a 5% price decrease from the previous one.
Max Position Increases (1-15) : number of Martingale orders to be executed after Start Martingale. For example, if you set 10, up to10 orders will be opened after Start Martingale.
Multiple For Position Increase (1-2x) : capital multiplier. For example, if you set 2 each for each new order, the capital involved will be doubled, order by order.
Take Profit Percentage (0.5-1000%) : percentage take profit, calculated on the average entry price.
2. Date Range Backtesting
The Date Range Backtesting section adjusts the analysis period. The user can easily adjust the UI parameters, and automatically the software will update the data.
LIMITATIONS OF THE MODEL
Although the Martingale model is widely used in position management, even this model has limitations and is subject to real risks during particular market conditions. Knowing these conditions will help you understand which asset is best to use the strategy on.
The main risks in adopting this automatic strategy are 2:
1) The price falls below our last order.
It happens during periods of strong bear-market in which the price collapses abruptly without experiencing any pullback. In this case the algorithm will enter a drawdown phase and the strategy will become a loser. The trader will then have to consider whether to wait for a price recovery or to incur a loss by manually closing the algorithm.
2) The price increases quickly.
It happens during periods of strong bull-market in which the price rises abruptly without experiencing any pullback. In this case the algorithm will not optimize order execution, working only with Start Martingale in the vast majority of trades. Given the exponential nature of the investment, the algorithm will in this case generate a profit that is always less than that of the reference market.
The best market conditions to use this strategy are characterized by high volatility such as correction phases during a bull run and/or markets that exhibit sideways price trends (such as areas of accumulation or congestion where price will generate many false signals).
FEATURES
This script was developed by including features to optimize the user experience.
Includes a dashboard at launch that allows the user to intuitively enter backtesting parameters.
Includes graphical indicator that helps the user analyze the behavior of the strategy.
Includes a date period backtesting feature that allows the user to adjust and choose custom historical periods.
DISCLAIMER
This script was released using parameters researched solely for the BTC/USDT pair, 4H timeframe, traded on the KuCoin Exchange (2017-present). Do not consider this combination of parameters as universal and usable on all assets and timeframes.
PresentTrend RMI Synergy - Strategy [presentTrading] █ Introduction and How it is Different
The "PresentTrend RMI Synergy Strategy" is the combined power of the Relative Momentum Index (RMI) and a custom presentTrend indicator. This strategy introduces a multifaceted approach, integrating momentum analysis with trend direction to offer traders a more nuanced and responsive trading mechanism.
BTCUSD 6h L/S Performance
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█ Strategy, How It Works: Detailed Explanation
The "PresentTrend RMI Synergy Strategy" intricately combines the Relative Momentum Index (RMI) and a custom SuperTrend indicator to create a powerful tool for traders.
🔶 Relative Momentum Index (RMI)
The RMI is a variation of the Relative Strength Index (RSI), but instead of using price closes against itself, it measures the momentum of up and down movements in price relative to previous prices over a given period. The RMI for a period length `N` is calculated as follows:
RMI = 100 - 100/ (1 + U/D)
where:
- `U` is the average upward price change over `N` periods,
- `D` is the average downward price change over `N` periods.
The RMI oscillates between 0 and 100, with higher values indicating stronger upward momentum and lower values suggesting stronger downward momentum.
RMI = 21
RMI = 42
For more information - RMI Trend Sync - Strategy :
🔶 presentTrend Indicator
The presentTrend indicator combines the Average True Range (ATR) with a moving average to determine trend direction and dynamic support or resistance levels. The presentTrend for a period length `M` and a multiplier `F` is defined as:
- Upper Band: MA + (ATR x F)
- Lower Band: MA - (ATR x F)
where:
- `MA` is the moving average of the close price over `M` periods,
- `ATR` is the Average True Range over the same period,
- `F` is the multiplier to adjust the sensitivity.
The trend direction switches when the price crosses the presentTrend bands, signaling potential entry or exit points.
presentTrend length = 3
presentTrend length = 10
For more information - PresentTrend - Strategy :
🔶 Strategy Logic
Entry Conditions:
- Long Entry: Triggered when the RMI exceeds a threshold, say 60, indicating a strong bullish momentum, and when the price is above the presentTrend, confirming an uptrend.
- Short Entry: Occurs when the RMI drops below a threshold, say 40, showing strong bearish momentum, and the price is below the present trend, indicating a downtrend.
Exit Conditions with Dynamic Trailing Stop:
- Long Exit: Initiated when the price crosses below the lower presentTrend band or when the RMI falls back towards a neutral level, suggesting a weakening of the bullish momentum.
- Short Exit: Executed when the price crosses above the upper presentTrend band or when the RMI rises towards a neutral level, indicating a reduction in bearish momentum.
Equations for Dynamic Trailing Stop:
- For Long Positions: The exit price is set at the lower SuperTrend band once the entry condition is met.
- For Short Positions: The exit price is determined by the upper SuperTrend band post-entry.
These dynamic trailing stops adjust as the market moves, providing a method to lock in profits while allowing room for the position to grow.
This strategy's strength lies in its dual analysis approach, leveraging RMI for momentum insights and presentTrend for trend direction and dynamic stops. This combination offers traders a robust framework to navigate various market conditions, aiming to capture trends early and exit positions strategically to maximize gains and minimize losses.
█ Trade Direction
The strategy provides flexibility in trade direction selection, offering "Long," "Short," or "Both" options to cater to different market conditions and trader preferences. This adaptability ensures that traders can align the strategy with their market outlook, risk tolerance, and trading goals.
█ Usage
To utilize the "PresentTrend RMI Synergy Strategy," traders should input their preferred settings in the Pine Script™ and apply the strategy to their charts. Monitoring RMI for momentum shifts and adjusting positions based on SuperTrend signals can optimize entry and exit points, enhancing potential returns while managing risk.
█ Default Settings
1. RMI Length: 21
The 21-period RMI length strikes a balance between capturing momentum and filtering out market noise, offering a medium-term outlook on market trends.
2. Super Trend Length: 7
A SuperTrend length of 7 periods is chosen for its responsiveness to price movements, providing a dynamic framework for trend identification without excessive sensitivity.
3. Super Trend Multiplier: 4.0
The multiplier of 4.0 for the SuperTrend indicator widens the trend bands, focusing on significant market moves and reducing the impact of minor fluctuations.
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The "PresentTrend RMI Synergy Strategy" represents a significant step forward in trading strategy development, blending momentum and trend analysis in a unique way. By providing a detailed framework for understanding market dynamics, this strategy empowers traders to make more informed decisions.
AI SuperTrend x Pivot Percentile - Strategy [PresentTrading]█ Introduction and How it is Different
The AI SuperTrend x Pivot Percentile strategy is a sophisticated trading approach that integrates AI-driven analysis with traditional technical indicators. Combining the AI SuperTrend with the Pivot Percentile strategy highlights several key advantages:
1. Enhanced Accuracy in Trend Prediction: The AI SuperTrend utilizes K-Nearest Neighbors (KNN) algorithm for trend prediction, improving accuracy by considering historical data patterns. This is complemented by the Pivot Percentile analysis which provides additional context on trend strength.
2. Comprehensive Market Analysis: The integration offers a multi-faceted approach to market analysis, combining AI insights with traditional technical indicators. This dual approach captures a broader range of market dynamics.
BTC 6H L/S Performance
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█ Strategy: How it Works - Detailed Explanation
🔶 AI-Enhanced SuperTrend Indicators
1. SuperTrend Calculation:
- The SuperTrend indicator is calculated using a moving average and the Average True Range (ATR). The basic formula is:
- Upper Band = Moving Average + (Multiplier × ATR)
- Lower Band = Moving Average - (Multiplier × ATR)
- The moving average type (SMA, EMA, WMA, RMA, VWMA) and the length of the moving average and ATR are adjustable parameters.
- The direction of the trend is determined based on the position of the closing price in relation to these bands.
2. AI Integration with K-Nearest Neighbors (KNN):
- The KNN algorithm is applied to predict trend direction. It uses historical price data and SuperTrend values to classify the current trend as bullish or bearish.
- The algorithm calculates the 'distance' between the current data point and historical points. The 'k' nearest data points (neighbors) are identified based on this distance.
- A weighted average of these neighbors' trends (bullish or bearish) is calculated to predict the current trend.
For more please check: Multi-TF AI SuperTrend with ADX - Strategy
🔶 Pivot Percentile Analysis
1. Percentile Calculation:
- This involves calculating the percentile ranks for high and low prices over a set of predefined lengths.
- The percentile function is typically defined as:
- Percentile = Value at (P/100) × (N + 1)th position
- Where P is the desired percentile, and N is the number of data points.
2. Trend Strength Evaluation:
- The calculated percentiles for highs and lows are used to determine the strength of bullish and bearish trends.
- For instance, a high percentile rank in the high prices may indicate a strong bullish trend, and vice versa for bearish trends.
For more please check: Pivot Percentile Trend - Strategy
🔶 Strategy Integration
1. Combining SuperTrend and Pivot Percentile:
- The strategy synthesizes the insights from both AI-enhanced SuperTrend and Pivot Percentile analysis.
- It compares the trend direction indicated by the SuperTrend with the strength of the trend as suggested by the Pivot Percentile analysis.
2. Signal Generation:
- A trading signal is generated when both the AI-enhanced SuperTrend and the Pivot Percentile analysis agree on the trend direction.
- For instance, a bullish signal is generated when both the SuperTrend is bullish, and the Pivot Percentile analysis shows strength in bullish trends.
🔶 Risk Management and Filters
- ADX and DMI Filter: The strategy uses the Average Directional Index (ADX) and the Directional Movement Index (DMI) as filters to assess the trend's strength and direction.
- Dynamic Trailing Stop Loss: Based on the SuperTrend indicator, the strategy dynamically adjusts stop-loss levels to manage risk effectively.
This strategy stands out for its ability to combine real-time AI analysis with established technical indicators, offering traders a nuanced and responsive tool for navigating complex market conditions. The equations and algorithms involved are pivotal in accurately identifying market trends and potential trade opportunities.
█ Usage
To effectively use this strategy, traders should:
1. Understand the AI and Pivot Percentile Indicators: A clear grasp of how these indicators work will enable traders to make informed decisions.
2. Interpret the Signals Accurately: The strategy provides bullish, bearish, and neutral signals. Traders should align these signals with their market analysis and trading goals.
3. Monitor Market Conditions: Given that this strategy is sensitive to market dynamics, continuous monitoring is crucial for timely decision-making.
4. Adjust Settings as Needed: Traders should feel free to tweak the input parameters to suit their trading preferences and to respond to changing market conditions.
█Default Settings and Their Impact on Performance
1. Trading Direction (Default: "Both")
Effect: Determines whether the strategy will take long positions, short positions, or both. Adjusting this setting can align the strategy with the trader's market outlook or risk preference.
2. AI Settings (Neighbors: 3, Data Points: 24)
Neighbors: The number of nearest neighbors in the KNN algorithm. A higher number might smooth out noise but could miss subtle, recent changes. A lower number makes the model more sensitive to recent data but may increase noise.
Data Points: Defines the amount of historical data considered. More data points provide a broader context but may dilute recent trends' impact.
3. SuperTrend Settings (Length: 10, Factor: 3.0, MA Source: "WMA")
Length: Affects the sensitivity of the SuperTrend indicator. A longer length results in a smoother, less sensitive indicator, ideal for long-term trends.
Factor: Determines the bandwidth of the SuperTrend. A higher factor creates wider bands, capturing larger price movements but potentially missing short-term signals.
MA Source: The type of moving average used (e.g., WMA - Weighted Moving Average). Different MA types can affect the trend indicator's responsiveness and smoothness.
4. AI Trend Prediction Settings (Price Trend: 10, Prediction Trend: 80)
Price Trend and Prediction Trend Lengths: These settings define the lengths of weighted moving averages for price and SuperTrend, impacting the responsiveness and smoothness of the AI's trend predictions.
5. Pivot Percentile Settings (Length: 10)
Length: Influences the calculation of pivot percentiles. A shorter length makes the percentile more responsive to recent price changes, while a longer length offers a broader view of price trends.
6. ADX and DMI Settings (ADX Length: 14, Time Frame: 'D')
ADX Length: Defines the period for the Average Directional Index calculation. A longer period results in a smoother ADX line.
Time Frame: Sets the time frame for the ADX and DMI calculations, affecting the sensitivity to market changes.
7. Commission, Slippage, and Initial Capital
These settings relate to transaction costs and initial investment, directly impacting net profitability and strategy feasibility.
Ichimoku Clouds Strategy Long and ShortOverview:
The Ichimoku Clouds Strategy leverages the Ichimoku Kinko Hyo technique to offer traders a range of innovative features, enhancing market analysis and trading efficiency. This strategy is distinct in its combination of standard methodology and advanced customization, making it suitable for both novice and experienced traders.
Unique Features:
Enhanced Interpretation: The strategy introduces weak, neutral, and strong bullish/bearish signals, enabling detailed interpretation of the Ichimoku cloud and direct chart plotting.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Dual Trading Modes: Long and Short modes are available, allowing alignment with market trends.
Flexible Risk Management: Offers three styles in each mode, combining fixed risk management with dynamic indicator states for versatile trade management.
Indicator Line Plotting: Enables plotting of Ichimoku indicator lines on the chart for visual decision-making support.
Methodology:
The strategy utilizes the standard Ichimoku Kinko Hyo model, interpreting indicator values with settings adjustable through a user-friendly menu. This approach is enhanced by TradingView's built-in strategy tester for customization and market selection.
Risk Management:
Our approach to risk management is dynamic and indicator-centric. With data from the last year, we focus on dynamic indicator states interpretations to mitigate manual setting causing human factor biases. Users still have the option to set a fixed stop loss and/or take profit per position using the corresponding parameters in settings, aligning with their risk tolerance.
Backtest Results:
Operating window: Date range of backtests is 2023.01.01 - 2024.01.04. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Maximum Single Position Loss: -6.29%
Maximum Single Profit: 22.32%
Net Profit: +10 901.95 USDT (+109.02%)
Total Trades: 119 (51.26% profitability)
Profit Factor: 1.775
Maximum Accumulated Loss: 4 185.37 USDT (-22.87%)
Average Profit per Trade: 91.67 USDT (+0.7%)
Average Trade Duration: 56 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. Backtest is calculated using deep backtest option in TradingView built-in strategy tester
How to Use:
Add the script to favorites for easy access.
Apply to the desired chart and timeframe (optimal performance observed on the 1H chart, ForEx or cryptocurrency top-10 coins with quote asset USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Backtesting ModuleDo you often find yourself creating new 'strategy()' scripts for each trading system? Are you unable to focus on generating new systems due to fatigue and time loss incurred in the process? Here's a potential solution: the 'Backtesting Module' :)
INTRODUCTION
Every trading system is based on four basic conditions: long entry, long exit, short entry and short exit (which are typically defined as boolean series in Pine Script).
If you can define the conditions generated by your trading system as a series of integers, it becomes possible to use these variables in different scripts in efficient ways. (Pine Script is a convenient language that allows you to use the integer output of one indicator as a source in another.)
The 'Backtesting Module' is a dynamic strategy script designed to adapt to your signals. It boasts two notable features:
⮞ It produces a backtest report using the entry and exit variables you define.
⮞ It not only serves for system testing but also to combine independent signals into a single system. (This functionality enables to create complex strategies and report on their success!)
The module tests Golden and Death cross signals by default, when you enter your own conditions the default signals will be neutralized. The methodology is described below.
PREPARATION
There are three simple steps to connect your own indicator to the Module.
STEP 1
Firstly, you must define entry and exit variables in your own script. Let's elucidate it with a straightforward example. Consider a system generating long and short signals based on the intersections of two moving averages. Consequently, our conditions would be as follows:
// Signals
long = ta.crossover(ta.sma(close, 14), ta.sma(close, 28))
short = ta.crossunder(ta.sma(close, 14), ta.sma(close, 28))
Now, the question is: How can we convert boolean variables into integer variables? The answer is conditional ternary block, defined as follows:
// Entry & Exit
long_entry = long ? 1 : 0
long_exit = short ? 1 : 0
short_entry = short ? 1 : 0
short_exit = long ? 1 : 0
The mechanics of the Entry & Exit variables are simple. The variable takes on a value of 1 when your trading system generates the signal and if your system does not produce any signal, variable returns 0. In this example, you see how exit signals can be generated in a trading system that only contains entry signals. If you have a system with original exit signals, you can also use them directly. (Please mind the NOTES section below).
STEP 2
To utilize the Entry & Exit variables as source in another script, they must be plotted on the chart. Therefore, the final detail to include in the script containing your trading system would be as follows:
// Plot The Output
plot(long_entry, "Long Entry", display=display.data_window, editable=false)
plot(long_exit, "Long Exit", display=display.data_window, editable=false)
plot(short_entry, "Short Entry", display=display.data_window, editable=false)
plot(short_exit, "Short Exit", display=display.data_window, editable=false)
STEP 3
Now, we are ready to test the system! Load the Backtesting Module indicator onto the chart along with your trading system/indicator. Then set the outputs of your system (Long Entry, Long Exit, Short Entry, Short Exit) as source in the module. That's it.
FEATURES & ORIGINALITY
⮞ Primarily, this script has been created to provide you with an easy and practical method when testing your trading system.
⮞ I thought it might be nice to visualize a few useful results. The Backtesting Module provides insights into the outcomes of both long and short trades by computing the number of trades and the success percentage.
⮞ Through the 'Trade' parameter, users can specify the market direction in which the indicator is permitted to initiate positions.
⮞ Users have the flexibility to define the date range for the test.
⮞ There are optional features allowing users to plot entry prices on the chart and customize bar colors.
⮞ The report and the test date range are presented in a table on the chart screen. The entry price can be monitored in the data window.
⮞ Note that results are based on realized returns, and the open trade is not included in the displayed results. (The only exception is the 'Unrealized PNL' result in the table.)
STRATEGY SETTINGS
The default parameters are as follows:
⮞ Initial Balance : 10000 (in units of currency)
⮞ Quantity : 10% of equity
⮞ Commission : 0.04%
⮞ Slippage : 0
⮞ Dataset : All bars in the chart
For a realistic backtest result, you should size trades to only risk sustainable amounts of equity. Do not risk more than 5-10% on a trade. And ALWAYS configure your commission and slippage parameters according to pessimistic scenarios!
NOTES
⮞ This script is intended solely for development purposes. And it'll will be available for all the indicators I publish.
⮞ In this version of the module, all order types are designed as market orders. The exit size is the sum of the entry size.
⮞ As your trading conditions grow more intricate, you might need to define the outputs of your system in alternative ways. The method outlined in this description is tailored for straightforward signal structures.
⮞ Additionally, depending on the structure of your trading system, the backtest module may require further development. This encompasses stop-loss, take-profit, specific exit orders, quantity, margin and risk management calculations. I am considering releasing improvements that consider these options in future versions.
⮞ An example of how complex trading signals can be generated is the OTT Collection. If you're interested in seeing how the signals are constructed, you can use the link below.
THANKS
Special thanks to PineCoders for their valuable moderation efforts.
I hope this will be a useful example for the TradingView community...
DISCLAIMER
This is just an indicator, nothing more. It is provided for informational and educational purposes exclusively. The utilization of this script does not constitute professional or financial advice. The user solely bears the responsibility for risks associated with script usage. Do not forget to manage your risk. And trade as safely as possible. Best of luck!
RMI Trend Sync - Strategy [presentTrading]█ Introduction and How It Is Different
The "RMI Trend Sync - Strategy " combines the strength of the Relative Momentum Index (RMI) with the dynamic nature of the Supertrend indicator. This strategy diverges from traditional methodologies by incorporating a dual analytical framework, leveraging both momentum and trend indicators to offer a more holistic market perspective. The integration of the RMI provides an enhanced understanding of market momentum, while the Super Trend indicator offers clear insights into the end of market trends, making this strategy particularly effective in diverse market conditions.
BTC 4h long/short performance
█ Strategy: How It Works - Detailed Explanation
- Understanding the Relative Momentum Index (RMI)
The Relative Momentum Index (RMI) is an adaptation of the traditional Relative Strength Index (RSI), designed to measure the momentum of price movements over a specified period. While RSI focuses on the speed and change of price movements, RMI incorporates the direction and magnitude of those movements, offering a more nuanced view of market momentum.
- Principle of RMI
Calculation Method: RMI is calculated by first determining the average gain and average loss over a given period (Length). It differs from RSI in that it uses the price change (close-to-close) rather than absolute gains or losses. The average gain is divided by the average loss, and this ratio is then normalized to fit within a 0-100 scale.
- Momentum Analysis in the Strategy
Thresholds for Decision Making: The strategy uses predetermined thresholds (pmom for positive momentum and nmom for negative momentum) to trigger trading decisions. When RMI crosses above the positive threshold and other conditions align (e.g., a bullish trend), it signals a potential long entry. Similarly, crossing below the negative threshold in a bearish trend may trigger a short entry.
- Super Trend and Trend Analysis
The Super Trend indicator is calculated based on a higher time frame, providing a broader view of the market trend. This indicator uses the Average True Range (ATR) to adapt to market volatility, making it an effective tool for identifying trend reversals.
The strategy employs a Volume Weighted Moving Average (VWMA) alongside the Super Trend, enhancing its capability to identify significant trend shifts.
ETH 4hr long/short performance
█ Trade Direction
The strategy offers flexibility in selecting the trading direction: long, short, or both. This versatility allows traders to adapt to their market outlook and risk tolerance, whether looking to capitalize on bullish trends, bearish trends, or a combination of both.
█ Usage
To effectively use the "RMI Trend Sync" strategy, traders should first set their preferred trading direction and adjust the RMI and Super Trend parameters according to their risk appetite and trading goals.
The strategy is designed to adapt to various market conditions, making it suitable for different asset classes and time frames.
█ Default Settings
RMI Settings: Length: 21, Positive Momentum Threshold: 70, Negative Momentum Threshold: 30
Super Trend Settings: Length: 10, Higher Time Frame: 480 minutes, Super Trend Factor: 3.5, MA Source: WMA
Visual Settings: Display Range MA: True, Bullish Color: #00bcd4, Bearish Color: #ff5252
Additional Settings: Band Length: 30, RWMA Length: 20
EUR/USD 45 MIN Strategy - FinexBOTThis strategy uses three indicators:
RSI (Relative Strength Index) - It indicates if a stock is potentially overbought or oversold.
CCI (Commodity Channel Index) - It measures the current price level relative to an average price level over a certain period of time.
Williams %R - It is a momentum indicator that shows whether a stock is at the high or low end of its trading range.
Long (Buy) Trades Open:
When all three indicators suggest that the stock is oversold (RSI is below 25, CCI is below -130, and Williams %R is below -85), the strategy will open a buy position, assuming there is no current open trade.
Short (Sell) Trades Open:
When all three indicators suggest the stock is overbought (RSI is above 75, CCI is above 130, and Williams %R is above -15), the strategy will open a sell position, assuming there is no current open trade.
SL (Stop Loss) and TP (Take Profit):
SL (Stop Loss) is 0.45%.
TP (Take Profit) is 1.2%.
The strategy automatically sets these exit points as a percentage of the entry price for both long and short positions to manage risks and secure profits. You can easily adopt these inputs according to your strategy. However, default settings are recommended.
2Mars - MA / BB / SuperTrend
The 2Mars strategy is a trading approach that aims to improve trading efficiency by incorporating several simple order opening tactics. These tactics include moving average crossovers, Bollinger Bands, and SuperTrend.
Entering a Position with the 2Mars Strategy:
Moving Average Crossover: This method considers the crossing of moving averages as a signal to enter a position.
Price Crossing Bollinger Bands: If the price crosses either the upper or lower Bollinger Band, it is seen as a signal to enter a position.
Price Crossing Moving Average: If the price crosses the moving average, it is also considered a signal to enter a position.
SuperTrend and Bars confirm:
The SuperTrend indicator is used to provide additional confirmation for entering positions and setting stop loss levels. "Bars confirm" is used only for entry to positions.
Moving Average Crossover Strategy:
A moving average crossover refers to the point on a chart where there is a crossover of the signal or fast moving average, above or below the basis or slow moving average. This strategy also uses moving averages for additional orders #3.
Basis Moving Average Length: Ratio * Multiplier
Signal Moving Average Length: Multiplier
Bollinger Bands:
Bollinger Bands consist of three bands: an upper band, a lower band, and a basis moving average. However, the 2Mars strategy incorporates multiple upper and lower levels for position entry and take profit.
Basis +/- StdDev * 0.618
Basis +/- StdDev * 1.618
Basis +/- StdDev * 2.618
Additional Orders:
Additional Order #1 and #2: closing price crosses above or below the Bollinger Bands.
Additional Order #3: closing price crosses above or below the basis or signal moving average.
Take Profit:
The strategy includes three levels for taking profits, which are based on the Bollinger Bands. Additionally, a percentage of the position can be chosen to close long or short positions.
Limit Orders:
The strategy allows for entering a position using a limit order. The calculation for the limit order involves the Average True Range (ATR) for a specific period.
For long positions: Low price - ATR * Multiplier
For short positions: High price + ATR * Multiplier
Stop Loss:
To manage risk, the strategy recommends using stop loss options. The stop loss is updated with each entry order and take-profit level 3. When using the SuperTrend Confirmation, the stop loss requires confirmation of a trend change. It allows for flexible adjustment of the stop loss when the trend changes.
There are three options for setting the stop loss:
1. ATR (Average True Range):
For long positions: Low price - ATR * Long multiplier
For short positions: High price + ATR * Short multiplier
2. SuperTrend + ATR:
For long positions: SuperTrend - ATR * Long multiplier
For short positions: SuperTrend + ATR * Short multiplier
3. StdDev:
For long positions: StdDev - ATR * Long multiplier
For short positions: StdDev + ATR * Short multiplier
Flexible Stop Loss:
There is also a flexible stop loss option for the ATR and StdDev methods. It is triggered when the SuperTrend or moving average trend changes unfavorably.
For long positions: Stop-loss price + (ATR * Long multiplier) * Multiplier
For short positions: Stop-loss price - (ATR * Short multiplier) * Multiplier
How configure:
Disable SuperTrend, take profit, stop loss, additional orders and begin setting up a strategy.
Pick soucre data
Number of bars for confirm
Pick up the ratio of the base moving average and the signal moving average.
Set up a SuperTrend
Time for set up of the Bollinger Bands and the take profit
And finaly set up of stop loss and limit orders
All done!
For OKX exchange:
TradingView.To Strategy Template (with Dyanmic Alerts)Hello traders,
If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further.
This Pine Script v5 strategy template is engineered for maximum customization and risk management.
Best part?
This Pine Script v5 template facilitates the dynamic construction of TradingView.TO alerts, sparing users the time and effort of mastering the TradingView.TO syntax and manually create alert commands.
This powerful tool gives much power to those who don't know how to code in Pinescript and want to automate their indicators' signals via TradingView.TO bot.
IMPORTANT NOTES
TradingView.TO is a trading bot software that forwards TradingView alerts to your brokers (examples: Binance, Oanda, Coinbase, Bybit, Metatrader 4/5, ...) for automating trading.
Many traders don't know how to create TradingView.TO dynamically-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly.
This script showcases how to create TradingView.TO alerts dynamically.
TRADINGVIEW ALERTS
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example: 1 alert for BTC/USDT on the 5 minutes chart, 1 alert for BTC/USDT on the 15-minute chart (assuming you want your bot to trade the BTC/USDT on the 5 and 15-minute timeframes)
2) Select the Order fills and alert() function calls condition
3) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
4) TradingView.TO uses webhook technology - setting a webhook URL from the alerts notifications tab is required.
KEY FEATURES
I) Modular Indicator Connection
* plug your existing indicator into the template.
* Only two lines of code are needed for full compatibility.
Step 1: Create your connector
Adapt your indicator with only 2 lines of code and then connect it to this strategy template.
To do so:
1) Find in your indicator where the conditions print the long/buy and short/sell signals.
2) Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator, whether a MACD , ZigZag, Pivots , higher-highs, lower-lows or whatever indicator with clear buy and sell conditions.
//@version=5
indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true)
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := barstate.isfirst ? na : supertrend
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none)
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr)
fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false)
fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false)
buy = ta.crossunder(direction, 0)
sell = ta.crossunder(direction, 0)
//////// CONNECTOR SECTION ////////
Signal = buy ? 1 : sell ? -1 : 0
plot(Signal, title = "Signal", display = display.data_window)
//////// CONNECTOR SECTION ////////
Important Notes
🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal
Now, you can connect your indicator to the Strategy Template using the method below or that one.
Step 2: Connect the connector
1) Add your updated indicator to a TradingView chart
2) Add the Strategy Template as well to the SAME chart
3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator)
Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember.
From then, you should start seeing the signals and plenty of other stuff on your chart.
🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time
II) BOT Risk Management:
- Max Drawdown:
Mode: Select whether the max drawdown is calculated in percentage (%) or USD.
Value: If the max drawdown reaches this specified value, set a value to halt the bot.
- Max Consecutive Days:
Use Max Consecutive Days BOT Halt: Enable/Disable halting the bot if the max consecutive losing days value is reached.
- Max Consecutive Days: Set the maximum number of consecutive losing days allowed before halting the bot.
- Max Losing Streak:
Use Max Losing Streak: Enable/Disable a feature to prevent the bot from taking too many losses in a row.
- Max Losing Streak Length: Set the maximum length of a losing streak allowed.
Margin Call:
- Use Margin Call: Enable/Disable a feature to exit when a specified percentage away from a margin call to prevent it.
Margin Call (%): Set the percentage value to trigger this feature.
- Close BOT Total Loss:
Use Close BOT Total Loss: Enable/Disable a feature to close all trades and halt the bot if the total loss is reached.
- Total Loss ($): Set the total loss value in USD to trigger this feature.
Intraday BOT Risk Management:
- Intraday Losses:
Use Intraday Losses BOT Halt: Enable/Disable halting the bot on reaching specified intraday losses.
Mode: Select whether the intraday loss is calculated in percentage (%) or USD.
- Max Intraday Losses (%): Set the value for maximum intraday losses.
Limit Intraday Trades:
- Use Limit Intraday Trades: Enable/Disable a feature to limit the number of intraday trades.
- Max Intraday Trades: Set the maximum number of intraday trades allowed.
Restart Intraday EA:
III) Order Types and Position Sizing
- Choose between market or limit orders.
- Set your position size directly in the template.
Please use the position size from the “Inputs” and not the “Properties” tab.
I know it's redundant. - the template needs this value from the "Inputs" tab to build the alerts, and the Backtester needs it from the "Properties" tab.
IV) Advanced Take-Profit and Stop-Loss Options
- Choose to set your SL/TP in either USD or percentages.
- Option for multiple take-profit levels and trailing stop losses.
- Move your stop loss to break even +/- offset in USD for “risk-free” trades.
V) Miscellaneous:
Retry order openings if they fail.
Order Types:
Select and specify order type and price settings.
Position Size:
Define the type and size of positions.
Leverage:
Leverage settings, including margin type and hedge mode.
Session:
Limit trades to specific sessions.
Dates:
Limit trades to a specific date range.
Trades Direction:
Direction: Specify the market direction for opening positions.
VI) Logger
The TradingView.TO commands are logged in the TradingView logger.
You'll find more information about it in this TradingView blog post .
WHY YOU MIGHT NEED THIS TEMPLATE
1) Transform your indicator into a TradingView.TO trading bot more easily than before
Connect your indicator to the template
Create your alerts
Set your EA settings
2) Save Time
Auto-generated alert messages for TradingView.TO.
I tested them all and checked with the support team what could/couldn’t be done.
3) Be in Control
Manage your trading risks with advanced features.
4) Customizable
Fits various trading styles and asset classes.
REQUIREMENTS
* Make sure you have your TradingView.TO account
* If there is any issue with the template, ask me in the comments section - I’ll answer quickly.
BACKTEST RESULTS FROM THIS POST
1) I connected this strategy template to a dummy Supertrend script.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with TradingView.TO.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :)
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
* Initial Capital: 100000 USD
* Position Size: 1%
* Commission Percent: 0.075%
* Slippage: 1 tick
* No margin/leverage used
ProfitView Strategy TemplateHello traders,
This script took me a full week of coding/testing, sweat, and tears - and I’m too nice as I’m giving it for free to the community.
If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further.
This Pine Script v5 strategy template is engineered for maximum customization and risk management.
Best part?
This Pine Script v5 template facilitates the dynamic construction of ProfitView alerts, sparing users the time and effort of mastering the ProfitView syntax and manually creating alert commands.
This powerful tool gives much power to those who don't know how to code in Pinescript and want to automate their indicators' signals via the ProfitView Chrome extension.
IMPORTANT NOTES
ProfitView is a trading bot software that forwards TradingView alerts to your brokers (examples: Binance, Oanda, Coinbase, Bybit, etc.) for automating trading.
Many traders don't know how to dynamically create ProfitView-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly.
This script showcases how to create ProfitView alerts dynamically.
TRADINGVIEW ALERTS
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example: 1 alert for EUR/USD on the 5 minutes chart, 1 alert for EUR/USD on the 15-minute chart (assuming you want your bot to trade the EUR/USD on the 5 and 15-minute timeframes)
2) Select the Order fills and alert() function calls condition
3) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
4) ProfitView doesn't use webhook technology, so setting a webhook URL from the alerts notifications tab is unnecessary.
KEY FEATURES
I) Modular Indicator Connection
* plug your existing indicator into the template.
* Only two lines of code are needed for full compatibility.
Step 1: Create your connector
Adapt your indicator with only 2 lines of code and then connect it to this strategy template.
To do so:
1) Find in your indicator where the conditions print the long/buy and short/sell signals.
2) Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator, whether a MACD , ZigZag, Pivots , higher-highs, lower-lows or whatever indicator with clear buy and sell conditions.
//@version=5
indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true)
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := barstate.isfirst ? na : supertrend
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none)
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr)
fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false)
fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false)
buy = ta.crossunder(direction, 0)
sell = ta.crossunder(direction, 0)
//////// CONNECTOR SECTION ////////
Signal = buy ? 1 : sell ? -1 : 0
plot(Signal, title = "Signal", display = display.data_window)
//////// CONNECTOR SECTION ////////
Important Notes
🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal
Now, you can connect your indicator to the Strategy Template using the method below or that one.
Step 2: Connect the connector
1) Add your updated indicator to a TradingView chart
2) Add the Strategy Template as well to the SAME chart
3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator)
Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember.
From then, you should start seeing the signals and plenty of other stuff on your chart.
🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time
II) BOT Risk Management:
- Max Drawdown:
Mode: Select whether the max drawdown is calculated in percentage (%) or USD.
Value: If the max drawdown reaches this specified value, set a value to halt the bot.
- Max Consecutive Days:
Use Max Consecutive Days BOT Halt: Enable/Disable halting the bot if the max consecutive losing days value is reached.
- Max Consecutive Days: Set the maximum number of consecutive losing days allowed before halting the bot.
- Max Losing Streak:
Use Max Losing Streak: Enable/Disable a feature to prevent the bot from taking too many losses in a row.
- Max Losing Streak Length: Set the maximum length of a losing streak allowed.
Margin Call:
- Use Margin Call: Enable/Disable a feature to exit when a specified percentage away from a margin call to prevent it.
Margin Call (%): Set the percentage value to trigger this feature.
- Close BOT Total Loss:
Use Close BOT Total Loss: Enable/Disable a feature to close all trades and halt the bot if the total loss is reached.
- Total Loss ($): Set the total loss value in USD to trigger this feature.
Intraday BOT Risk Management:
- Intraday Losses:
Use Intraday Losses BOT Halt: Enable/Disable halting the bot on reaching specified intraday losses.
Mode: Select whether the intraday loss is calculated in percentage (%) or USD.
- Max Intraday Losses (%): Set the value for maximum intraday losses.
Limit Intraday Trades:
- Use Limit Intraday Trades: Enable/Disable a feature to limit the number of intraday trades.
- Max Intraday Trades: Set the maximum number of intraday trades allowed.
Restart Intraday EA:
- Use Restart Intraday EA: Enable/Disable a feature to restart the bot at the first bar of the next day if it has been stopped with an intraday risk management safeguard.
III) Order Types and Position Sizing
- Choose between market, limit, or stop orders.
- Set your position size directly in the template.
Please use the position size from the “Inputs” and not the “Properties” tab.
I know it's redundant. - the template needs this value from the "Inputs" tab to build the alerts, and the Backtester needs it from the "Properties" tab.
IV) Advanced Take-Profit and Stop-Loss Options
- Choose to set your SL/TP in either pips or percentages.
- Option for multiple take-profit levels and trailing stop losses.
- Move your stop loss to break even +/- offset in pips for “risk-free” trades.
V) Miscellaneous
Retry order openings if they fail.
Order Types:
Select and specify order type and price settings.
Position Size:
Define the type and size of positions.
Leverage:
Leverage settings, including margin type and hedge mode.
Session:
Limit trades to specific sessions.
Dates:
Limit trades to a specific date range.
Trades Direction:
Direction: Specify the market direction for opening positions.
VI) Notifications (Telegram/Discord/Email/IFTTT/Twilio/SMS)
Customize notifications sent to Telegram, Discord, Email, IFTTT, Twilio, and ProfitView Logger.
VII) Logger
The ProfitView commands are logged in the TradingView logger.
You'll find more information about it in this TradingView blog post .
WHY YOU MIGHT NEED THIS TEMPLATE
1) Transform your indicator into a ProfitView trading bot more easily than before
Connect your indicator to the template
Create your alerts
Set your EA settings
2) Save Time
Auto-generated alert messages for ProfitView.
I tested them all and checked with the support team what could/couldn’t be done.
3) Be in Control
Manage your trading risks with advanced features.
4) Customizable
Fits various trading styles and asset classes.
REQUIREMENTS
* Make sure you have your ProfitView account and do the settings correctly in your Chrome extension. If you don't know how to do it, read the documentation + ask for help in the ProfitView Discord support channel.
* If there is any issue with the template, ask me in the comments section - I’ll answer quickly.
BACKTEST RESULTS FROM THIS POST
1) I connected this strategy template to a dummy Supertrend script.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with ProfitView.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :)
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
* Initial Capital: 100000 USD
* Position Size: 1%
* Commission Percent: 0.075%
* Slippage: 1 tick
* No margin/leverage used
Best regards,
Dave
Adaptive SMI Ergodic StrategyThe Adaptive SMI Ergodic Strategy aims to capture the momentum and direction of a financial asset by leveraging the Stochastic Momentum Index Indicator (SMI) in an ergodic form. The strategy uses two lengths for the SMI, a shorter and a longer one, and an Exponential Moving Average (EMA) to serve as the signal line. Additionally, the strategy incorporates customizable overbought and oversold thresholds to improve the probability of successful trade execution.
How It Works:
Long Entry: A long position is taken when the ergodic SMI crosses over the EMA signal line, and both the SMI and EMA are below the oversold threshold.
Short Entry: A short position is initiated when the ergodic SMI crosses under the EMA signal line, and both the SMI and EMA are above the overbought threshold.
The strategy plots the SMI in yellow and the EMA signal line in purple. Horizontal lines indicate the overbought and oversold thresholds, and a colored background helps in visually identifying these zones.
Parameters:
Long Length: The length of the long EMA in SMI calculation.
Short Length: The length of the short EMA in SMI calculation.
Signal Line Length: The length for the EMA serving as the signal line.
Oversold: Customizable threshold for the oversold condition.
Overbought: Customizable threshold for the overbought condition.
Historical Context: The SMI Indicator
The Stochastic Momentum Index (SMI) was developed by William Blau in the early 1990s as an enhancement to traditional stochastic oscillators. The SMI provides a range of values like a traditional stochastic, but it differs in that it calculates the distance of the current close relative to the median of the high/low range, as opposed to the close relative to the low. As a result, the SMI is less erratic and more responsive, offering a clearer picture of market trends.
In recent years, the SMI has been adapted into ergodic forms to facilitate smoother data analysis, reduce lag, and improve trading accuracy. The Adaptive SMI Ergodic Strategy leverages these modern enhancements to offer a more robust, customizable trading strategy that aligns with various market conditions.
3kilos BTC 15mThe "3kilos BTC 15m" is a comprehensive trading strategy designed to work on a 15-minute timeframe for Bitcoin (BTC) or other cryptocurrencies. This strategy combines multiple indicators, including Triple Exponential Moving Averages (TEMA), Average True Range (ATR), and Heikin-Ashi candlesticks, to generate buy and sell signals. It also incorporates risk management features like take profit and stop loss.
Indicators
Triple Exponential Moving Averages (TEMA): Three TEMA lines are used with different lengths and sources:
Short TEMA (Red) based on highs
Long TEMA 1 (Blue) based on lows
Long TEMA 2 (Green) based on closing prices
Average True Range (ATR): Custom ATR calculation with EMA smoothing is used for volatility measurement.
Supertrend: Calculated using ATR and a multiplier to determine the trend direction.
Simple Moving Average (SMA): Applied to the short TEMA to smooth out its values.
Heikin-Ashi Close: Used for additional trend confirmation.
Entry & Exit Conditions
Long Entry: Triggered when the short TEMA is above both long TEMA lines, the Supertrend is bullish, the short TEMA is above its SMA, and the Heikin-Ashi close is higher than the previous close.
Short Entry: Triggered when the short TEMA is below both long TEMA lines, the Supertrend is bearish, the short TEMA is below its SMA, and the Heikin-Ashi close is lower than the previous close.
Take Profit and Stop Loss: Both are calculated as a percentage of the entry price, and they are set for both long and short positions.
Risk Management
Take Profit: Set at 1% above the entry price for long positions and 1% below for short positions.
Stop Loss: Set at 3% below the entry price for long positions and 3% above for short positions.
Commission and Pyramiding
Commission: A 0.07% commission is accounted for in the strategy.
Pyramiding: The strategy does not allow pyramiding.
Note
This strategy is designed for educational purposes and should not be considered as financial advice. Always do your own research and consider consulting a financial advisor before engaging in trading.
Trend Confirmation StrategyThe profitability and uniqueness of a trading strategy depend on various factors including market conditions, risk management, and the strategy's ability to capitalize on price movements. I'll describe the strategy provided and highlight its potential benefits and differences compared to other strategies:
Strategy Overview:
The provided strategy combines three technical indicators: Supertrend, MACD, and VWAP. It aims to identify potential entry and exit points by confirming trend direction and considering the proximity to the VWAP level. The strategy also incorporates stop-loss and take-profit mechanisms, as well as a trailing stop.
Unique Aspects and Potential Benefits:
Trend Confirmation: The strategy uses both Supertrend and MACD to confirm the trend direction. This dual confirmation can increase the likelihood of accurate trend identification and filter out false signals.
VWAP Confirmation: The strategy considers the proximity of the price to the VWAP level. This dynamic level can act as a support or resistance and provide additional context for entry decisions.
Adaptive Stop Loss: The strategy sets a stop-loss range, which helps provide some tolerance for minor price fluctuations. This adaptive approach considers market volatility and helps prevent premature stop-loss triggers.
Trailing Stop: The strategy incorporates a trailing stop mechanism to lock in profits as the trade moves in the desired direction. This can potentially enhance profitability during strong trends.
Partial Profit Booking: While not explicitly implemented in the provided code, you could consider booking partial profits when the MACD shows a crossover in the opposite direction. This aspect could help secure gains while still keeping exposure to potential further price movements.
Key Differences from Other Strategies:
Dual Indicator Confirmation: The combination of Supertrend and MACD for trend confirmation is a unique aspect of this strategy. It adds an extra layer of filtering to enhance the accuracy of entry signals.
Dynamic VWAP: Incorporating the VWAP level into the decision-making process adds a dynamic element to the strategy. VWAP is often used by institutional traders, and its inclusion can provide insights into the market sentiment.
Adaptive Stop Loss and Trailing: The strategy's use of an adaptive stop-loss range and a trailing stop can help manage risk and protect profits more effectively during changing market conditions.
Partial Profit Booking: The suggestion to consider partial profit booking upon MACD crossovers in the opposite direction is a practical approach to secure gains while staying in the trade.
Caution and Considerations:
Backtesting: Before deploying any strategy in real trading, it's crucial to thoroughly backtest it on historical data to understand its performance under various market conditions.
Risk Management: While the strategy has built-in risk management mechanisms, it's essential to carefully manage position sizes and overall portfolio risk.
Market Conditions: No strategy works well in all market conditions. It's important to be flexible and adjust the strategy or refrain from trading during particularly volatile or unpredictable periods.
Continuous Monitoring: Even though the strategy includes automated components, continuous monitoring of the trades and market conditions is necessary.
Adaptability: Markets can change over time. Traders need to be prepared to adapt the strategy as necessary to stay aligned with evolving market dynamics.
