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The S02 strategy is a backtesting strategy that uses the Parabolic SAR (PSAR) indicator as a trailing stop loss. It is designed to be adaptable to different trading strategies. Here are the important parts of the strategy:
Timeframe: The strategy operates on 1-hour candlestick data.
Stoploss: The stop loss is set to -0.2, indicating a 20% loss limit.
Custom Info: This is a dictionary used to store custom information for each trading pair.
Use Custom Stoploss: This flag is set to True, indicating that the strategy uses a custom stop loss implementation. The strategy consists of the following functions: custom_stoploss: This function calculates the custom stop loss based on the PSAR indicator. It retrieves the PSAR value from the analyzed dataframe and calculates the new stop loss relative to the current rate. The result is returned as a relative negative offset. populate_indicators: This function populates the PSAR indicator in the dataframe. It also stores the PSAR values in the custom_info dictionary for backtesting and hyperopt. populate_buy_trend: This function defines the buy signal for the strategy. It checks if the PSAR value is smaller than the PSAR value of the previous candle, indicating a buy opportunity. The 'buy' column in the dataframe is set to 1 for the corresponding rows. populate_sell_trend: This function defines the sell signal for the strategy. In this case, the sell signal is deactivated, and the 'sell' column is set to 0 for all rows. Overall, the S02 strategy uses the PSAR indicator to generate buy signals based on specific conditions, and it has a custom stop loss implementation.
Stoploss: The stop loss is set to -0.2, indicating a 20% loss limit.
Custom Info: This is a dictionary used to store custom information for each trading pair.
Use Custom Stoploss: This flag is set to True, indicating that the strategy uses a custom stop loss implementation. The strategy consists of the following functions: custom_stoploss: This function calculates the custom stop loss based on the PSAR indicator. It retrieves the PSAR value from the analyzed dataframe and calculates the new stop loss relative to the current rate. The result is returned as a relative negative offset. populate_indicators: This function populates the PSAR indicator in the dataframe. It also stores the PSAR values in the custom_info dictionary for backtesting and hyperopt. populate_buy_trend: This function defines the buy signal for the strategy. It checks if the PSAR value is smaller than the PSAR value of the previous candle, indicating a buy opportunity. The 'buy' column in the dataframe is set to 1 for the corresponding rows. populate_sell_trend: This function defines the sell signal for the strategy. In this case, the sell signal is deactivated, and the 'sell' column is set to 0 for all rows. Overall, the S02 strategy uses the PSAR indicator to generate buy signals based on specific conditions, and it has a custom stop loss implementation.
stoploss: -0.2 timeframe: 1h hash(sha256): 5130e91e82e780ada05dc52526720c230251fee0512a2e71a9cb7ca6c7b36bf3
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last change: 2022-07-02 19:54:08