bbrsi_2

The "bbrsi" strategy is a backtesting strategy for trading. It uses various technical indicators to determine when to buy and sell assets. Here is a breakdown of how the strategy works: Ticker Interval: The strategy operates on 15-minute ticker intervals.

ROI Table: The strategy has predefined return on investment (ROI) targets at different time intervals.

For example, after 0 minutes, the target ROI is 0.24991, after 120 minutes it is 0.15395, after 201 minutes it is 0.05842, and after 555 minutes the target ROI is 0.

Stoploss: The strategy defines a stoploss threshold at -0.13159, which indicates the maximum acceptable loss before selling. Trailing Stop: The strategy uses a trailing stop mechanism. If the asset price moves positively by 1.011% (trailing_stop_positive), the trailing stop is activated. The trailing stop offset is set at 5.334% (trailing_stop_positive_offset), meaning that the stop loss will be adjusted at that percentage below the highest price since the trailing stop was activated. Indicators: The strategy populates several indicators using the Ta-Lib and qtpylib libraries: RSI (Relative Strength Index) MFI (Money Flow Index) Bollinger Bands (four sets with different standard deviations) Buy Signal: The strategy generates a buy signal when the asset's closing price falls below the lower band of the first set of Bollinger Bands (bb_lowerband1). Sell Signal: The strategy generates a sell signal when the asset's RSI value exceeds 56 and the closing price rises above the upper band of the third set of Bollinger Bands (bb_upperband3). Note: Some conditions in the code are commented out (e.g., RSI and MFI checks), indicating that they are not currently active but can be enabled if needed. Overall, the strategy aims to identify potential buying opportunities when the price is below the lower Bollinger Band and selling opportunities when the price exceeds the upper Bollinger Band and the RSI value is high.