The BB_RPB_3c strategy is a backtesting strategy that utilizes various technical indicators to generate buy signals. Here is a brief description of what the strategy does:
It calculates Bollinger Bands with a window of 20 and 2 standard deviations on the typical price of the asset. It adds the lower, middle, and upper Bollinger Bands to the dataframe.
It calculates the width of the Bollinger Bands as a percentage of the middle band.
It calculates the absolute difference between the current close price and the previous close price.
It calculates the Simple Moving Average (SMA) with a time period of 9. It calculates the Commodity Channel Index (CCI) with a length of 20. It calculates the Exponential Moving Averages (EMA) with time periods of 8, 14, 20, 50, and 200. It calculates the Hull Moving Average (HMA) with a window of 50. It calculates the Relative Strength Index (RSI) with time periods of 14, 4, 20, 6, 8, 84, and 112. It calculates the Elder's Force Index (EWO) with a short period of 50 and a long period of 200. It calculates the Stochastic Fast %K and %D with periods of 5, 3, 0, 3, and 0. It calculates the Average Directional Index (ADX). It calculates the Heikin-Ashi candles, including open, close, high, and low prices. It calculates Bollinger Bands with a window of 40 and 2 standard deviations on the Heikin-Ashi typical price. It calculates the absolute difference between the middle and lower Bollinger Bands. It calculates the absolute difference between the current Heikin-Ashi close price and the previous close price. It calculates the absolute difference between the Heikin-Ashi close price and the Heikin-Ashi low price. It calculates the EMA with a time period of 50 on the Heikin-Ashi close prices. It calculates the Rate of Change Ratio (ROCR) with a time period of 28 on the Heikin-Ashi close prices. It calculates the Williams %R with a period of 14. It calculates the T3 indicator. It calculates the Volume Weighted Average Price (VWAP) with a window of 20 and standard deviation of 1. It calculates the average of the close, open, high, and low prices. It calculates the Money Flow Index (MFI) with a default time period. It calculates multiple exponential moving averages (EMAs) with different time periods on the dataframe. It retrieves an informative timeframe (1 hour) data for the same trading pair and merges it with the current dataframe. It applies additional buy signal conditions based on various indicators and their respective thresholds. This strategy aims to identify potential buying opportunities based on the specified conditions and technical indicators.