The DualThrustStrategy is a trading strategy implemented in Python using the Freqtrade library for backtesting purposes. Here's a description of what the strategy does:
The strategy calculates the Dual Thrust levels based on a given range and uses them as thresholds for entering and exiting trades. The range is calculated using the highest and lowest prices within a specified time frame.
The strategy has the following parameters: ROI table: Specifies the desired return on investment for different time periods.
Stoploss: Defines the maximum acceptable loss percentage for a trade.
Trailing stop: Enables trailing stop functionality to secure profits as the price moves in the desired direction. Timeframe: Sets the time frame for data analysis (e.g., 5 minutes). Can short: Allows short selling if set to True. The strategy's main logic is implemented in three methods: populate_indicators: This method calculates the Dual Thrust levels and additional indicators such as the moving average (MA) using the provided price data. populate_entry_trend: This method determines when to enter a long or short position based on specific conditions, including the calculated Dual Thrust levels and the moving average. populate_exit_trend: This method identifies the exit points for both long and short positions by considering the Dual Thrust levels and previous price data. Throughout the strategy, the calculated Dual Thrust levels (BuyLine and SellLine) play a crucial role in determining the entry and exit signals. The strategy aims to capture price movements that surpass these thresholds, indicating potential buying or selling opportunities. Please note that the provided code snippet includes some commented out sections that could potentially contain additional indicators or logic for trend following. However, they are not currently active in the strategy implementation.
The strategy has the following parameters: ROI table: Specifies the desired return on investment for different time periods.
Stoploss: Defines the maximum acceptable loss percentage for a trade.
Trailing stop: Enables trailing stop functionality to secure profits as the price moves in the desired direction. Timeframe: Sets the time frame for data analysis (e.g., 5 minutes). Can short: Allows short selling if set to True. The strategy's main logic is implemented in three methods: populate_indicators: This method calculates the Dual Thrust levels and additional indicators such as the moving average (MA) using the provided price data. populate_entry_trend: This method determines when to enter a long or short position based on specific conditions, including the calculated Dual Thrust levels and the moving average. populate_exit_trend: This method identifies the exit points for both long and short positions by considering the Dual Thrust levels and previous price data. Throughout the strategy, the calculated Dual Thrust levels (BuyLine and SellLine) play a crucial role in determining the entry and exit signals. The strategy aims to capture price movements that surpass these thresholds, indicating potential buying or selling opportunities. Please note that the provided code snippet includes some commented out sections that could potentially contain additional indicators or logic for trend following. However, they are not currently active in the strategy implementation.
stoploss: -0.265 timeframe: 5m hash(sha256): 464c54bbe4823c355994adb16e38a6768e19f3787d1915081e53ac61aad0ae69 indicators: high ma 111low close date open low dataframedate
No similar strategies found. (based on used indicators)
last change: 2024-04-29 01:21:42