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The given code represents a trading strategy based on Bollinger Bands and the Relative Strength Index (RSI). Here's a description of what the strategy does:
The strategy consists of two main functions: populate_indicators and populate_buy_trend (for generating buy signals) and populate_sell_trend (for generating sell signals). These functions are part of a class called Bb which implements the IStrategy interface.
In the populate_indicators function, various Bollinger Bands are calculated using the qtpylib library and added as columns to the input dataframe.
Bollinger Bands are volatility bands placed above and below a moving average.
In this strategy, Bollinger Bands with standard deviations of 1, 2, 3, and 4 are calculated and stored in different columns. The populate_buy_trend function generates buy signals based on certain conditions. First, if enabled, it checks if the RSI value is below a specified threshold. Then, based on the value of buy_bb_value, it compares the closing price of the asset with the lower band of the corresponding Bollinger Band. If the conditions are met, a 'buy' signal is indicated by setting the 'buy' column to 1 in the dataframe. Similarly, the populate_sell_trend function generates sell signals. If enabled, it checks if the RSI value is above a specified threshold. Then, based on the value of sell_bb_value, it compares the closing price of the asset with the lower, middle, or upper band of the corresponding Bollinger Band. If the conditions are met, a 'sell' signal is indicated by setting the 'sell' column to 1 in the dataframe. Overall, this strategy combines Bollinger Bands and RSI to generate buy and sell signals based on the specified conditions and indicators.
In the populate_indicators function, various Bollinger Bands are calculated using the qtpylib library and added as columns to the input dataframe.
Bollinger Bands are volatility bands placed above and below a moving average.
In this strategy, Bollinger Bands with standard deviations of 1, 2, 3, and 4 are calculated and stored in different columns. The populate_buy_trend function generates buy signals based on certain conditions. First, if enabled, it checks if the RSI value is below a specified threshold. Then, based on the value of buy_bb_value, it compares the closing price of the asset with the lower band of the corresponding Bollinger Band. If the conditions are met, a 'buy' signal is indicated by setting the 'buy' column to 1 in the dataframe. Similarly, the populate_sell_trend function generates sell signals. If enabled, it checks if the RSI value is above a specified threshold. Then, based on the value of sell_bb_value, it compares the closing price of the asset with the lower, middle, or upper band of the corresponding Bollinger Band. If the conditions are met, a 'sell' signal is indicated by setting the 'sell' column to 1 in the dataframe. Overall, this strategy combines Bollinger Bands and RSI to generate buy and sell signals based on the specified conditions and indicators.
startup_candle_count : 30 bb_lowerband_1sd: -0.036% bb_middleband_1sd: -0.042% bb_upperband_1sd: -0.048% bb_lowerband_2sd: -0.030% bb_middleband_2sd: -0.042% bb_upperband_2sd: -0.054% bb_lowerband_3sd: -0.024% bb_middleband_3sd: -0.042% bb_upperband_3sd: -0.060% bb_lowerband_4sd: -0.018% bb_middleband_4sd: -0.042% bb_upperband_4sd: -0.066%
stoploss: -0.327 timeframe: 5m hash(sha256): 3f8eb0abebd9eb670a725f10cf4cd03309c411bff6c473881e2b754c4c4a7120 indicators: bb_lowerband_3sd upper mid lower bb_upperband_3sd bb_lowerband_4sd bb_middleband_3sd bb_middleband_1sd bb_lowerband_2sd bb_upperband_2sd bb_upperband_4sd rsi close bb_middleband_4sd bb_middleband_2sd bb_lowerband_1sd tr_bb_lower_1sd tr_bb_lower_2sd tr_bb_lower_3sd tr_bb_lower_4sd bb_upperband_1sd
No similar strategies found. (based on used indicators)
last change: 2023-08-02 13:51:03