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The strategy implemented in this code is called SMAOffsetProtectOptV1. Here is a short description of what it does:
The strategy uses a combination of moving averages (MA) and offset values to generate buy and sell signals. It calculates multiple MA values for buying and selling based on the specified parameters.
It uses the Exponential Moving Average (EMA) indicator from the TA-Lib library to calculate the MA values.
It also calculates the Elliott Wave Oscillator (EWO) and Relative Strength Index (RSI) indicators.
For buying, the strategy looks for conditions where the closing price is below the MA multiplied by a specified low offset value, and the EWO and RSI values meet certain criteria. It also checks for conditions where the closing price is below the MA multiplied by a low offset value and the EWO value is below a specified threshold. For selling, the strategy looks for conditions where the closing price is above the MA multiplied by a specified high offset value. The strategy supports trailing stop and sell signal options. It can be optimized using hyperparameters such as base_nb_candles_buy, base_nb_candles_sell, low_offset, high_offset, ewo_low, ewo_high, and rsi_buy. The strategy operates on candlestick data with a timeframe of 5 minutes and uses 1-hour timeframe data for informative purposes. It populates indicators such as MA, EWO, and RSI in the dataframe to be used for generating signals. The strategy defines the minimal ROI (return on investment) and stop-loss values. It also provides options for customizing the plot configuration. This strategy aims to backtest and automate trading decisions based on the specified indicators and conditions, allowing users to evaluate its performance and profitability.
It uses the Exponential Moving Average (EMA) indicator from the TA-Lib library to calculate the MA values.
It also calculates the Elliott Wave Oscillator (EWO) and Relative Strength Index (RSI) indicators.
For buying, the strategy looks for conditions where the closing price is below the MA multiplied by a specified low offset value, and the EWO and RSI values meet certain criteria. It also checks for conditions where the closing price is below the MA multiplied by a low offset value and the EWO value is below a specified threshold. For selling, the strategy looks for conditions where the closing price is above the MA multiplied by a specified high offset value. The strategy supports trailing stop and sell signal options. It can be optimized using hyperparameters such as base_nb_candles_buy, base_nb_candles_sell, low_offset, high_offset, ewo_low, ewo_high, and rsi_buy. The strategy operates on candlestick data with a timeframe of 5 minutes and uses 1-hour timeframe data for informative purposes. It populates indicators such as MA, EWO, and RSI in the dataframe to be used for generating signals. The strategy defines the minimal ROI (return on investment) and stop-loss values. It also provides options for customizing the plot configuration. This strategy aims to backtest and automate trading decisions based on the specified indicators and conditions, allowing users to evaluate its performance and profitability.
stoploss: -0.5 timeframe: 5m hash(sha256): e3bcfae4bb4fe651fc79a9032a8de199e7f728e99631a40fd9b91718d10295c3 indicators: rsi_buy ma_sell_val volume EWO ewo_high low_offset close ewo_low rsi high_offset base_nb_candles_sell base_nb_candles_buy ma_buy_val
No similar strategies found. (based on used indicators)
last change: 2023-04-26 07:24:48