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The EnsembleStrategy is a trading strategy that combines multiple individual strategies to make buy decisions in backtesting. Here is a breakdown of its important parts:
populate_indicators: This method is responsible for populating the indicators used by the strategy. In this implementation, it doesn't modify the dataframe and simply returns it as is.
populate_buy_trend: This method generates buy signals based on the combined strategies.
It iterates through a list of strategy names and retrieves each strategy's indicators.
It then generates buy signals for each strategy and adds them as columns to the dataframe. Finally, it calculates an overall buy signal by taking the mean of the strategy-specific buy signals and comparing it to a threshold. populate_sell_trend: This method sets the initial sell signal to 0 for all rows in the dataframe. It doesn't modify the dataframe further. stoploss_from_open: This function calculates a custom stop-loss value based on the current profit and predefined parameters. It considers different profit thresholds (PF_1 and PF_2) and corresponding stop-loss values (SL_1 and SL_2) to determine the appropriate stop-loss value. __call__: This is the main method of the strategy that is called when determining the stop-loss value. It takes inputs such as the trading pair, current trade information, current time, rate, and profit. It uses the predefined parameters (sell_HSL, sell_PF_1, sell_SL_1, sell_PF_2, sell_SL_2) to calculate the stop-loss value based on the current profit. The strategy combines multiple individual strategies by generating buy signals for each strategy and aggregating them into an overall buy signal. It also calculates a custom stop-loss value based on the current profit and predefined parameters.
populate_buy_trend: This method generates buy signals based on the combined strategies.
It iterates through a list of strategy names and retrieves each strategy's indicators.
It then generates buy signals for each strategy and adds them as columns to the dataframe. Finally, it calculates an overall buy signal by taking the mean of the strategy-specific buy signals and comparing it to a threshold. populate_sell_trend: This method sets the initial sell signal to 0 for all rows in the dataframe. It doesn't modify the dataframe further. stoploss_from_open: This function calculates a custom stop-loss value based on the current profit and predefined parameters. It considers different profit thresholds (PF_1 and PF_2) and corresponding stop-loss values (SL_1 and SL_2) to determine the appropriate stop-loss value. __call__: This is the main method of the strategy that is called when determining the stop-loss value. It takes inputs such as the trading pair, current trade information, current time, rate, and profit. It uses the predefined parameters (sell_HSL, sell_PF_1, sell_SL_1, sell_PF_2, sell_SL_2) to calculate the stop-loss value based on the current profit. The strategy combines multiple individual strategies by generating buy signals for each strategy and aggregating them into an overall buy signal. It also calculates a custom stop-loss value based on the current profit and predefined parameters.
Unable to parse Traceback (Logfile Exceeded Limit)
stoploss: -0.99 timeframe: 5m hash(sha256): e7fb1ea9f0211ef0f230377b16ba4f50daf2e9022f1fed13dd088f124e273ae1 indicators: f"strat_buy_signal_strategy_name sell buy
No similar strategies found. (based on used indicators)
last change: 2024-07-28 01:28:40