The BBRSI strategy is a trading strategy implemented in the Python programming language using the Freqtrade bot framework. The strategy combines two technical indicators, Bollinger Bands (BB) and Relative Strength Index (RSI), to generate buy and sell signals. Here's a breakdown of the strategy:
Import necessary libraries and modules:
talib.abstract as ta: This module provides various technical analysis indicators.
pandas: A library for data manipulation and analysis.
freqtrade.vendor.qtpylib.indicators as qtpylib: Additional indicators provided by Freqtrade.
Define the BBRSI class, which implements the Freqtrade IStrategy interface. Set the strategy's parameters: minimal_roi: A dictionary specifying the minimum return on investment (ROI) at different time intervals. ticker_interval: The desired interval for ticker data (e.g., '1h' for 1-hour intervals). order_types: An optional mapping of order types for different actions (buy, sell, stop loss). order_time_in_force: An optional mapping of time in force for orders. Implement the populate_indicators method: This method adds technical indicators to the DataFrame. It calculates the RSI (Relative Strength Index) using the ta.RSI function. It calculates the Bollinger Bands using the qtpylib.bollinger_bands function and adds the upper, middle, and lower bands to the DataFrame. Implement the populate_buy_trend method: This method populates the 'buy' column in the DataFrame based on the defined buy conditions. The buy condition checks if the close price is below the lower Bollinger Band (bb_lowerband3). Implement the populate_sell_trend method: This method populates the 'sell' column in the DataFrame based on the defined sell conditions. The sell condition checks if the RSI is above 75 and the close price is above the middle Bollinger Band (bb_middleband). The strategy aims to generate buy signals when the price is below the lower Bollinger Band and sell signals when the RSI is high and the price is above the middle Bollinger Band. The specific parameters and thresholds can be adjusted according to the trader's preferences and market conditions.
pandas: A library for data manipulation and analysis.
freqtrade.vendor.qtpylib.indicators as qtpylib: Additional indicators provided by Freqtrade.
Define the BBRSI class, which implements the Freqtrade IStrategy interface. Set the strategy's parameters: minimal_roi: A dictionary specifying the minimum return on investment (ROI) at different time intervals. ticker_interval: The desired interval for ticker data (e.g., '1h' for 1-hour intervals). order_types: An optional mapping of order types for different actions (buy, sell, stop loss). order_time_in_force: An optional mapping of time in force for orders. Implement the populate_indicators method: This method adds technical indicators to the DataFrame. It calculates the RSI (Relative Strength Index) using the ta.RSI function. It calculates the Bollinger Bands using the qtpylib.bollinger_bands function and adds the upper, middle, and lower bands to the DataFrame. Implement the populate_buy_trend method: This method populates the 'buy' column in the DataFrame based on the defined buy conditions. The buy condition checks if the close price is below the lower Bollinger Band (bb_lowerband3). Implement the populate_sell_trend method: This method populates the 'sell' column in the DataFrame based on the defined sell conditions. The sell condition checks if the RSI is above 75 and the close price is above the middle Bollinger Band (bb_middleband). The strategy aims to generate buy signals when the price is below the lower Bollinger Band and sell signals when the RSI is high and the price is above the middle Bollinger Band. The specific parameters and thresholds can be adjusted according to the trader's preferences and market conditions.
Traceback (most recent call last): File "/freqtrade/freqtrade/main.py", line 42, in main return_code = args['func'](args) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/commands/optimize_commands.py", line 57, in start_backtesting backtesting = Backtesting(config) ^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 114, in __init__ validate_config_consistency(self.config) File "/freqtrade/freqtrade/configuration/config_validation.py", line 95, in validate_config_consistency validate_config_schema(conf, preliminary=preliminary) File "/freqtrade/freqtrade/configuration/config_validation.py", line 65, in validate_config_schema raise ValidationError( jsonschema.exceptions.ValidationError: 'stoploss' is a required property
stoploss: 0 timeframe: 1h hash(sha256): 9bb41c19610a3ab5d2c69c8fd62acd35622fa86cf6f1972e7d90f549406f73e9 indicators: upper mid lower bb_middleband3 bb_upperband3 bb_middleband rsi close bb_upperband bb_lowerband bb_lowerband3
No similar strategies found. (based on used indicators)
last change: 2024-04-28 05:30:18