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The RsiStrat strategy is a backtesting strategy that uses the Relative Strength Index (RSI) indicator to generate buy and sell signals for trading. Here is a breakdown of how the strategy works:
Timeframe and Candle Count: The strategy operates on a daily timeframe and requires at least 25 candles before generating valid signals. ROI (Return on Investment) Settings: The strategy defines the minimal_roi dictionary, which specifies different levels of return on investment at different time intervals.
For example, a 1-hour return of 0.01 (1%) is expected, a 30-minute return of 0.03 (3%), a 20-minute return of 0.04 (4%), and a 0-minute return of 0.05 (5%).
Stop Loss: The strategy sets a stop loss of -0.10 (-10%) to limit potential losses.
Trailing Stop: The trailing_stop parameter is set to False, indicating that the strategy does not use a trailing stop feature. Sell Signals: The use_sell_signal parameter is set to True, enabling the strategy to generate sell signals. Buy and Sell RSI Parameters: The strategy defines two integer parameters, buy_rsi and sell_rsi, which determine the RSI thresholds for generating buy and sell signals, respectively. The buy_rsi parameter ranges from 5 to 30, with a default value of 20, while the sell_rsi parameter ranges from 75 to 95, with a default value of 85. Indicator Calculation: The populate_indicators function calculates the RSI indicator using the ta.RSI() function from the talib library. The RSI values are stored in the 'RSI' column of the dataframe. Buy Signal Generation: The populate_buy_trend function generates buy signals based on the condition that the RSI value is below the buy_rsi threshold. Sell Signal Generation: The populate_sell_trend function generates sell signals based on the condition that the RSI value is above the sell_rsi threshold. Overall, the RsiStrat strategy aims to identify buying opportunities when the RSI is below a certain threshold and selling opportunities when the RSI is above a certain threshold. It employs predefined ROI levels and a stop loss to manage risk and potential profits.
For example, a 1-hour return of 0.01 (1%) is expected, a 30-minute return of 0.03 (3%), a 20-minute return of 0.04 (4%), and a 0-minute return of 0.05 (5%).
Stop Loss: The strategy sets a stop loss of -0.10 (-10%) to limit potential losses.
Trailing Stop: The trailing_stop parameter is set to False, indicating that the strategy does not use a trailing stop feature. Sell Signals: The use_sell_signal parameter is set to True, enabling the strategy to generate sell signals. Buy and Sell RSI Parameters: The strategy defines two integer parameters, buy_rsi and sell_rsi, which determine the RSI thresholds for generating buy and sell signals, respectively. The buy_rsi parameter ranges from 5 to 30, with a default value of 20, while the sell_rsi parameter ranges from 75 to 95, with a default value of 85. Indicator Calculation: The populate_indicators function calculates the RSI indicator using the ta.RSI() function from the talib library. The RSI values are stored in the 'RSI' column of the dataframe. Buy Signal Generation: The populate_buy_trend function generates buy signals based on the condition that the RSI value is below the buy_rsi threshold. Sell Signal Generation: The populate_sell_trend function generates sell signals based on the condition that the RSI value is above the sell_rsi threshold. Overall, the RsiStrat strategy aims to identify buying opportunities when the RSI is below a certain threshold and selling opportunities when the RSI is above a certain threshold. It employs predefined ROI levels and a stop loss to manage risk and potential profits.
stoploss: -0.1 timeframe: 1d hash(sha256): 176346ebd0804c656067415ddd9b9f0a3a6479c86e55547cebaaf1df1c5ae9f3
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last change: 2022-07-10 22:37:05