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The EnsembleStrategyV1 class is a backtesting strategy that combines multiple trading strategies to generate buy and sell signals. It follows the IStrategy interface. Here's a breakdown of its key methods:
populate_indicators: This method takes a DataFrame and a metadata dictionary as input and returns the same DataFrame.
It is responsible for populating any necessary indicators in the DataFrame for the strategy.
In this implementation, it does not modify the DataFrame and simply returns it unchanged.
populate_buy_trend: This method populates the buy signals in the DataFrame based on the combination of buy strategies defined in the buy_strategies attribute. It iterates over each strategy, retrieves the strategy object, calculates the strategy indicators using the advise_indicators method, and adds the buy signals to the DataFrame. The final buy signal is determined by taking the mean of the buy signals from all the strategies and comparing it to the buy_mean_threshold value. If the mean is greater than the threshold, it is considered a buy signal. populate_sell_trend: This method works similarly to populate_buy_trend, but it populates the sell signals instead. It iterates over the sell strategies, retrieves the strategy object, calculates the strategy indicators, and adds the sell signals to the DataFrame. The final sell signal is determined by taking the mean of the sell signals from all the strategies and comparing it to the sell_mean_threshold value. If the mean is greater than the threshold, it is considered a sell signal. In summary, the EnsembleStrategyV1 class combines multiple trading strategies, calculates their respective indicators, and generates buy and sell signals based on the combination of these strategies. The final signals are determined by comparing the mean of the individual strategy signals to predefined thresholds.
It is responsible for populating any necessary indicators in the DataFrame for the strategy.
In this implementation, it does not modify the DataFrame and simply returns it unchanged.
populate_buy_trend: This method populates the buy signals in the DataFrame based on the combination of buy strategies defined in the buy_strategies attribute. It iterates over each strategy, retrieves the strategy object, calculates the strategy indicators using the advise_indicators method, and adds the buy signals to the DataFrame. The final buy signal is determined by taking the mean of the buy signals from all the strategies and comparing it to the buy_mean_threshold value. If the mean is greater than the threshold, it is considered a buy signal. populate_sell_trend: This method works similarly to populate_buy_trend, but it populates the sell signals instead. It iterates over the sell strategies, retrieves the strategy object, calculates the strategy indicators, and adds the sell signals to the DataFrame. The final sell signal is determined by taking the mean of the sell signals from all the strategies and comparing it to the sell_mean_threshold value. If the mean is greater than the threshold, it is considered a sell signal. In summary, the EnsembleStrategyV1 class combines multiple trading strategies, calculates their respective indicators, and generates buy and sell signals based on the combination of these strategies. The final signals are determined by comparing the mean of the individual strategy signals to predefined thresholds.
stoploss: -0.203 timeframe: 1h hash(sha256): 093baefc4abd0f5bf500e9607c8e0f5007f52884bf1394bb11d2300f0092e4a8 indicators: f"strat_buy_signal_strategy_name sell f"strat_sell_signal_strategy_name buy
No similar strategies found. (based on used indicators)
last change: 2024-04-29 01:17:11