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The DevilStra strategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It is designed for backtesting purposes on a backtesting website. The strategy consists of three main components: populating indicators, populating buy trends, and populating sell trends.
In the populate_indicators method, the strategy takes a DataFrame and metadata as inputs and returns the populated DataFrame.
However, in this implementation, the method simply returns the original DataFrame without any modifications.
The populate_buy_trend method populates the buy trend in the DataFrame based on specific conditions. It retrieves a list of whitelisted trading pairs and determines the index of the current pair in the list. It also retrieves buy spells and their corresponding parameters based on the pair index. Then, it generates conditions using the provided indicators, crossed indicators, operators, and numerical values. The conditions are appended to a list, and if there are any conditions present, the DataFrame is updated accordingly by setting the 'buy' column to 1 for rows that meet all the conditions. Similarly, the populate_sell_trend method populates the sell trend in the DataFrame. It follows a similar process as the populate_buy_trend method, but with sell spells and parameters. It's important to note that if the number of whitelisted pairs exceeds the number of buy or sell spells, a warning message is printed, suggesting the need to re-hyperopt the strategy and make appropriate adjustments. Overall, the DevilStra strategy generates buy and sell signals based on specific conditions derived from indicators and their corresponding parameters, allowing for backtesting and evaluation of its effectiveness.
In the populate_indicators method, the strategy takes a DataFrame and metadata as inputs and returns the populated DataFrame.
However, in this implementation, the method simply returns the original DataFrame without any modifications.
The populate_buy_trend method populates the buy trend in the DataFrame based on specific conditions. It retrieves a list of whitelisted trading pairs and determines the index of the current pair in the list. It also retrieves buy spells and their corresponding parameters based on the pair index. Then, it generates conditions using the provided indicators, crossed indicators, operators, and numerical values. The conditions are appended to a list, and if there are any conditions present, the DataFrame is updated accordingly by setting the 'buy' column to 1 for rows that meet all the conditions. Similarly, the populate_sell_trend method populates the sell trend in the DataFrame. It follows a similar process as the populate_buy_trend method, but with sell spells and parameters. It's important to note that if the number of whitelisted pairs exceeds the number of buy or sell spells, a warning message is printed, suggesting the need to re-hyperopt the strategy and make appropriate adjustments. Overall, the DevilStra strategy generates buy and sell signals based on specific conditions derived from indicators and their corresponding parameters, allowing for backtesting and evaluation of its effectiveness.
stoploss: -0.28 timeframe: 4h hash(sha256): 3fd994557200ac051046ea86b1197c4c1422e7227ae3672b3207c35a0aee3175 indicators: sell_crossed_indicator2 indicator_trend_sma sell_operator2 crossed_indicator sell_crossed_indicator1 sell_real_num1 indicator buy_indicator1 buy_real_num2 buy_indicator0 sell_operator1 sell_indicator2 volume buy_operator0 sell_indicator1 buy_indicator2 sell_indicator0 sharp_indicator buy_crossed_indicator2 sell_crossed_indicator0 buy_operator2 buy_real_num1 buy_crossed_indicator1 buy_operator1 sell_real_num0 buy_crossed_indicator0 sell_operator0 sell_real_num2 buy_real_num0
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last change: 2024-04-28 14:35:56