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The strategy, named "SwingHighToSky," is a trading strategy implemented in Python using the Freqtrade library. Here is a description of what the strategy does:
The strategy uses the 5-minute timeframe for trading. It sets a stop loss value of -0.34338, indicating the maximum acceptable loss before exiting a trade.
The minimal return on investment (ROI) targets are defined as follows: 0% ROI at the start of the trade (time = 0) 0.15058 ROI at 33 time intervals 0.0453 ROI at 64 time intervals 0.02333 ROI at 244 time intervals The strategy uses several technical indicators, including the Commodity Channel Index (CCI) and Relative Strength Index (RSI).
Here are the parameters for these indicators: CCI: Buy time period: 72 Buy value: -175 Sell time period: 66 Sell value: -106 RSI: Buy time period: 36 Buy value: 90 Sell time period: 45 Sell value: 88 The strategy involves the following steps: Populating indicators: The strategy calculates the CCI and RSI values for the given time periods using the ta.CCI and ta.RSI functions.
The calculated values are stored in the dataframe. Populating buy trend: The strategy identifies buying opportunities based on the following conditions: CCI value (time period = 72) is less than -175. RSI value (time period = 36) is less than 90. If both conditions are met, a 'buy' signal is generated and marked as 1 in the dataframe. Populating sell trend: The strategy identifies selling opportunities based on the following conditions: CCI value (time period = 66) is greater than -106. RSI value (time period = 45) is greater than 88. If both conditions are met, a 'sell' signal is generated and marked as 1 in the dataframe. Please note that this description provides a brief overview of the strategy's key components and steps. Further analysis and testing are recommended before using it in a live trading environment.
The minimal return on investment (ROI) targets are defined as follows: 0% ROI at the start of the trade (time = 0) 0.15058 ROI at 33 time intervals 0.0453 ROI at 64 time intervals 0.02333 ROI at 244 time intervals The strategy uses several technical indicators, including the Commodity Channel Index (CCI) and Relative Strength Index (RSI).
Here are the parameters for these indicators: CCI: Buy time period: 72 Buy value: -175 Sell time period: 66 Sell value: -106 RSI: Buy time period: 36 Buy value: 90 Sell time period: 45 Sell value: 88 The strategy involves the following steps: Populating indicators: The strategy calculates the CCI and RSI values for the given time periods using the ta.CCI and ta.RSI functions.
The calculated values are stored in the dataframe. Populating buy trend: The strategy identifies buying opportunities based on the following conditions: CCI value (time period = 72) is less than -175. RSI value (time period = 36) is less than 90. If both conditions are met, a 'buy' signal is generated and marked as 1 in the dataframe. Populating sell trend: The strategy identifies selling opportunities based on the following conditions: CCI value (time period = 66) is greater than -106. RSI value (time period = 45) is greater than 88. If both conditions are met, a 'sell' signal is generated and marked as 1 in the dataframe. Please note that this description provides a brief overview of the strategy's key components and steps. Further analysis and testing are recommended before using it in a live trading environment.
startup_candle_count : 50 Recursive Analysis found no issues while using 50 startup_candle_count
stoploss: -0.343 timeframe: 5m hash(sha256): bdf71be87974bab10f4d701d6eb264299668e0fd7033bef9c084f2493a0ebce4 indicators: rsistrrsiSellTP ccistrcciSellTP rsistrrsiBuyTP ccistrcciBuyTP
No similar strategies found. (based on used indicators)
last change: 2023-08-25 12:44:16