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The Devil strategy is a backtesting strategy implemented as a class. It is designed to populate buy and sell signals based on specified conditions. Here is a breakdown of what the strategy does:
populate_indicators function: This function takes a DataFrame and metadata as input and returns the same DataFrame.
It is responsible for populating any indicators required by the strategy.
In the given code, this function does not modify the DataFrame and simply returns it as is.
populate_buy_trend function: This function populates the buy signals in the DataFrame based on specified conditions. Here are the important steps: It retrieves the current whitelist of pairs and determines the index of the current pair being processed. It splits the buy spell (a set of parameters) into individual parameters. It checks if the number of pairs is greater than the number of buy spells. If so, it prints an error message and exits the program. It retrieves the specific buy parameters for the current pair index. It generates conditions based on the buy indicators, crossed indicators, operators, and real numbers specified in the parameters. It appends the generated condition to a list of conditions. If there are any conditions, it applies them to the DataFrame by setting the 'buy' column to 1 for rows that satisfy all the conditions. Finally, it returns the modified DataFrame. populate_sell_trend function: This function is similar to populate_buy_trend but populates the sell signals in the DataFrame. Here are the important steps: It follows the same steps as populate_buy_trend for retrieving sell parameters and generating conditions. It appends the generated condition to a list of conditions. If there are any conditions, it applies them to the DataFrame by setting the 'sell' column to 1 for rows that satisfy all the conditions. Finally, it returns the modified DataFrame. Overall, the Devil strategy takes a DataFrame as input, populates any required indicators, generates buy and sell signals based on specified conditions, and modifies the DataFrame accordingly.
It is responsible for populating any indicators required by the strategy.
In the given code, this function does not modify the DataFrame and simply returns it as is.
populate_buy_trend function: This function populates the buy signals in the DataFrame based on specified conditions. Here are the important steps: It retrieves the current whitelist of pairs and determines the index of the current pair being processed. It splits the buy spell (a set of parameters) into individual parameters. It checks if the number of pairs is greater than the number of buy spells. If so, it prints an error message and exits the program. It retrieves the specific buy parameters for the current pair index. It generates conditions based on the buy indicators, crossed indicators, operators, and real numbers specified in the parameters. It appends the generated condition to a list of conditions. If there are any conditions, it applies them to the DataFrame by setting the 'buy' column to 1 for rows that satisfy all the conditions. Finally, it returns the modified DataFrame. populate_sell_trend function: This function is similar to populate_buy_trend but populates the sell signals in the DataFrame. Here are the important steps: It follows the same steps as populate_buy_trend for retrieving sell parameters and generating conditions. It appends the generated condition to a list of conditions. If there are any conditions, it applies them to the DataFrame by setting the 'sell' column to 1 for rows that satisfy all the conditions. Finally, it returns the modified DataFrame. Overall, the Devil strategy takes a DataFrame as input, populates any required indicators, generates buy and sell signals based on specified conditions, and modifies the DataFrame accordingly.
stoploss: -0.28 timeframe: 4h hash(sha256): 31c6e0888a1065b7428a76c0da3d598cac4e53bbd8d069a5a2675de59a3d73f0
Was not able to fetch indicators from Strategyfile.
last change: 2022-07-11 00:41:32