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The "SwingHighToSky" strategy is a trading strategy implemented in Python for backtesting purposes. It is designed to be used with the Freqtrade library. Here's a brief description of what the strategy does:
The strategy uses the 15-minute timeframe for analyzing price data.
The stop loss for this strategy is set at -0.34338, which means that if the price falls below this threshold, the position will be automatically closed to limit losses.
The strategy defines a set of target returns for different holding periods, called "minimal_roi." These target returns are percentages and are defined for specific time intervals after entering a position.
The strategy relies on two technical indicators: CCI (Commodity Channel Index) and RSI (Relative Strength Index) for making buy and sell decisions. For the buy signal, the strategy checks if the CCI value (with a time period specified by the "buy_cciTime" parameter) is below a certain threshold ("buy_cci") AND if the RSI value (with a time period specified by the "buy_rsiTime" parameter) is below a certain threshold ("buy_rsi"). For the sell signal, the strategy checks if the CCI value (with a time period specified by the "sell_cciTime" parameter) is above a certain threshold ("sell_cci") AND if the RSI value (with a time period specified by the "sell_rsiTime" parameter) is above a certain threshold ("sell_rsi"). The strategy allows for optimization of the parameters through a parameter space defined by the minimum and maximum values of the respective indicators. The strategy also provides a set of default parameter values for the buy and sell signals, which can be used as a starting point for optimization. The strategy uses the populate_indicators method to calculate the CCI and RSI values for different time periods and adds them as additional columns to the input dataframe. The populate_buy_trend method populates the "buy" column in the dataframe with a value of 1 if the buy conditions are met based on the CCI and RSI values. The populate_sell_trend method populates the "sell" column in the dataframe with a value of 1 if the sell conditions are met based on the CCI and RSI values. Please note that this is just a brief overview of the strategy, and there may be additional details and considerations that are not mentioned here.
The stop loss for this strategy is set at -0.34338, which means that if the price falls below this threshold, the position will be automatically closed to limit losses.
The strategy defines a set of target returns for different holding periods, called "minimal_roi." These target returns are percentages and are defined for specific time intervals after entering a position.
The strategy relies on two technical indicators: CCI (Commodity Channel Index) and RSI (Relative Strength Index) for making buy and sell decisions. For the buy signal, the strategy checks if the CCI value (with a time period specified by the "buy_cciTime" parameter) is below a certain threshold ("buy_cci") AND if the RSI value (with a time period specified by the "buy_rsiTime" parameter) is below a certain threshold ("buy_rsi"). For the sell signal, the strategy checks if the CCI value (with a time period specified by the "sell_cciTime" parameter) is above a certain threshold ("sell_cci") AND if the RSI value (with a time period specified by the "sell_rsiTime" parameter) is above a certain threshold ("sell_rsi"). The strategy allows for optimization of the parameters through a parameter space defined by the minimum and maximum values of the respective indicators. The strategy also provides a set of default parameter values for the buy and sell signals, which can be used as a starting point for optimization. The strategy uses the populate_indicators method to calculate the CCI and RSI values for different time periods and adds them as additional columns to the input dataframe. The populate_buy_trend method populates the "buy" column in the dataframe with a value of 1 if the buy conditions are met based on the CCI and RSI values. The populate_sell_trend method populates the "sell" column in the dataframe with a value of 1 if the sell conditions are met based on the CCI and RSI values. Please note that this is just a brief overview of the strategy, and there may be additional details and considerations that are not mentioned here.
stoploss: -0.343 timeframe: 15m hash(sha256): d93dd83b9f350dbad15cac88a8f4cce9132607eaf92ad09078c96662325cb187 indicators: ccival rsisellval rsival ccisellval
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last change: 2023-08-16 02:14:10