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The ReinforcedAverageStrategy is a trading strategy implemented in Python for backtesting purposes. The strategy is based on simple crossover signals and serves as a proof of concept rather than a high-performing strategy. Here's a breakdown of its key components:
The strategy uses two exponential moving averages (EMAs) as indicators: maShort with a time period of 8 and maMedium with a time period of 21.
Additional indicators are calculated for graphing purposes, including Bollinger Bands (bb_lowerband, bb_upperband, bb_middleband) with a window of 20 and 2 standard deviations.
The strategy also includes a longer timeframe (resample_2880_sma) for comparison, which is the 50-period simple moving average (SMA) on a resampled dataframe with a ticker interval of 4 hours.
The populate_buy_trend function determines the buy signal by checking for a crossover where maShort crosses above maMedium, the closing price is above the resampled SMA, and the volume is greater than 0. The populate_sell_trend function determines the sell signal by checking for a crossover where maMedium crosses above maShort and the volume is greater than 0. Additionally, the strategy defines certain parameters and settings such as minimal_roi (minimal return on investment), stoploss (optimal stop loss), trailing_stop (trailing stop loss feature), and ticker_interval (the preferred interval for ticker data). However, these values may be overridden if specified in the configuration file. Please note that the strategy is described as not performing well and is mainly used as a proof of concept.
Additional indicators are calculated for graphing purposes, including Bollinger Bands (bb_lowerband, bb_upperband, bb_middleband) with a window of 20 and 2 standard deviations.
The strategy also includes a longer timeframe (resample_2880_sma) for comparison, which is the 50-period simple moving average (SMA) on a resampled dataframe with a ticker interval of 4 hours.
The populate_buy_trend function determines the buy signal by checking for a crossover where maShort crosses above maMedium, the closing price is above the resampled SMA, and the volume is greater than 0. The populate_sell_trend function determines the sell signal by checking for a crossover where maMedium crosses above maShort and the volume is greater than 0. Additionally, the strategy defines certain parameters and settings such as minimal_roi (minimal return on investment), stoploss (optimal stop loss), trailing_stop (trailing stop loss feature), and ticker_interval (the preferred interval for ticker data). However, these values may be overridden if specified in the configuration file. Please note that the strategy is described as not performing well and is mainly used as a proof of concept.
stoploss: -0.2 timeframe: 4h hash(sha256): f1e4c6e001b4771dd5b09fcedf84f88f6dceecf9bbeafb3b68fa6c105f410274
Was not able to fetch indicators from Strategyfile.
last change: 2023-06-30 11:45:59