The strategy implemented in this code is called "BinHV45". It is a trading strategy that uses Bollinger Bands as a technical indicator to generate buy signals. Here is a brief explanation of what the strategy does:
It calculates the Bollinger Bands using the stock price data, with a specified window size and number of standard deviations.
The strategy defines certain parameters for buy signals, such as df_close_bbdelta, df_close_closedelta, and df_tail_bbdelta.
It populates additional indicators in the dataframe, including 'mid' (the middle Bollinger Band value), 'lower' (the lower Bollinger Band value), 'bbdelta' (the absolute difference between 'mid' and 'lower'), 'pricedelta' (the absolute difference between open and close prices), 'closedelta' (the absolute difference between consecutive close prices), and 'tail' (the absolute difference between close and low prices).
The populate_buy_trend method identifies buy signals based on certain conditions, including the previous lower Bollinger Band being greater than 0, 'bbdelta' being greater than a fraction of the current close price ('df_close_bbdelta'), 'closedelta' being greater than a fraction of the current close price ('df_close_closedelta'), 'tail' being less than a fraction of 'bbdelta' ('df_tail_bbdelta'), and specific price conditions. The populate_sell_trend method does not generate any sell signals. The strategy sets a minimal return on investment (ROI) and a stop-loss value. The timeframe used for analyzing the data is 1 minute. Please note that this description is a simplified explanation of the strategy's functionality.
The strategy defines certain parameters for buy signals, such as df_close_bbdelta, df_close_closedelta, and df_tail_bbdelta.
It populates additional indicators in the dataframe, including 'mid' (the middle Bollinger Band value), 'lower' (the lower Bollinger Band value), 'bbdelta' (the absolute difference between 'mid' and 'lower'), 'pricedelta' (the absolute difference between open and close prices), 'closedelta' (the absolute difference between consecutive close prices), and 'tail' (the absolute difference between close and low prices).
The populate_buy_trend method identifies buy signals based on certain conditions, including the previous lower Bollinger Band being greater than 0, 'bbdelta' being greater than a fraction of the current close price ('df_close_bbdelta'), 'closedelta' being greater than a fraction of the current close price ('df_close_closedelta'), 'tail' being less than a fraction of 'bbdelta' ('df_tail_bbdelta'), and specific price conditions. The populate_sell_trend method does not generate any sell signals. The strategy sets a minimal return on investment (ROI) and a stop-loss value. The timeframe used for analyzing the data is 1 minute. Please note that this description is a simplified explanation of the strategy's functionality.
stoploss: -0.05 timeframe: 1m hash(sha256): 1eb054a9ee3d6ca50567d51a45f5a80d101204730bf7c60225ce6aaf05466303 indicators: mid lower pricedelta close closedelta tail open low bbdelta
No similar strategies found. (based on used indicators)
last change: 2024-05-02 09:40:56