The "TaSearch30m" strategy is a backtesting strategy designed for trading on a 30-minute timeframe. It uses technical analysis indicators and specific conditions to determine buy and sell signals. The strategy first imports the necessary libraries and modules, including pandas for data manipulation and a custom module called "TaSearch" for performing technical analysis searches.
The strategy has two main methods for populating indicators: "buy_past_rsi" and "buy_stride." These methods iterate over the given DataFrame in reverse order and apply certain conditions to identify potential buying opportunities based on past relative strength index (RSI) values and price extremes.
The "buy_past_rsi" method looks for instances where the RSI value is below 25 within a specified time window, while the "buy_stride" method considers RSI values between 30 and 45 and looks for price extremes that meet certain criteria.
These methods update the DataFrame with additional columns indicating the buying conditions. The strategy also has methods for populating buy and sell trends: "populate_buy_trend" and "populate_sell_trend." These methods use the indicators generated by the previous methods and apply specific conditions to determine when to initiate a buy or sell signal. In this case, the strategy sets the "buy" signal when the "buy_stride" value is greater than 1, the "buy_past_rsi" value is greater than 4, and the "market" value is -1. The "sell" signal is set when the RSI value exceeds 85. Overall, the strategy combines various technical analysis indicators and conditions to generate buy and sell signals based on past price behavior and RSI values.
The strategy has two main methods for populating indicators: "buy_past_rsi" and "buy_stride." These methods iterate over the given DataFrame in reverse order and apply certain conditions to identify potential buying opportunities based on past relative strength index (RSI) values and price extremes.
The "buy_past_rsi" method looks for instances where the RSI value is below 25 within a specified time window, while the "buy_stride" method considers RSI values between 30 and 45 and looks for price extremes that meet certain criteria.
These methods update the DataFrame with additional columns indicating the buying conditions. The strategy also has methods for populating buy and sell trends: "populate_buy_trend" and "populate_sell_trend." These methods use the indicators generated by the previous methods and apply specific conditions to determine when to initiate a buy or sell signal. In this case, the strategy sets the "buy" signal when the "buy_stride" value is greater than 1, the "buy_past_rsi" value is greater than 4, and the "market" value is -1. The "sell" signal is set when the RSI value exceeds 85. Overall, the strategy combines various technical analysis indicators and conditions to generate buy and sell signals based on past price behavior and RSI values.
stoploss: -0.07 timeframe: 30m hash(sha256): fc291dfdbe7478e4ac84c90a8b83184d70f2adf00cd0ec68cecc9b9f09246571
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last change: 2024-04-28 15:10:29