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The "CMCWinner" strategy is a sample strategy designed for backtesting trading strategies. It utilizes various technical indicators to generate buy and sell signals based on specific conditions. Indicators used:
Commodity Channel Index (CCI): Identifies overbought conditions when CCI > 100 and oversold conditions when CCI < -100.
Money Flow Index (MFI): Measures the strength of money flowing in and out of a security.
The strategy considers a buy signal when MFI < 20.
Chande Momentum Oscillator (CMO): Measures the momentum of a security's price. The strategy considers a buy signal when CMO < -50. The strategy defines the following: "minimal_roi": A dictionary specifying the desired return on investment (ROI) at different stages. For example, the strategy aims for a 2% ROI when 30% of the target ROI is achieved. "stoploss": Specifies the desired stop-loss value for the strategy, which is set at -5%. "ticker_interval": Defines the time interval for the ticker data, set to 15 minutes. The strategy's main functions are: "populate_indicators": Calculates the values of the selected technical indicators (CCI, MFI, CMO) and adds them as columns to the provided DataFrame. "populate_buy_trend": Generates a buy signal by checking if the previous values of CCI, MFI, and CMO meet specific criteria. "populate_sell_trend": Generates a sell signal by checking if the previous values of CCI, MFI, and CMO meet specific criteria. Note: This is a sample strategy provided as a starting point, and you can customize it by adding more indicators and methods to suit your specific needs.
Money Flow Index (MFI): Measures the strength of money flowing in and out of a security.
The strategy considers a buy signal when MFI < 20.
Chande Momentum Oscillator (CMO): Measures the momentum of a security's price. The strategy considers a buy signal when CMO < -50. The strategy defines the following: "minimal_roi": A dictionary specifying the desired return on investment (ROI) at different stages. For example, the strategy aims for a 2% ROI when 30% of the target ROI is achieved. "stoploss": Specifies the desired stop-loss value for the strategy, which is set at -5%. "ticker_interval": Defines the time interval for the ticker data, set to 15 minutes. The strategy's main functions are: "populate_indicators": Calculates the values of the selected technical indicators (CCI, MFI, CMO) and adds them as columns to the provided DataFrame. "populate_buy_trend": Generates a buy signal by checking if the previous values of CCI, MFI, and CMO meet specific criteria. "populate_sell_trend": Generates a sell signal by checking if the previous values of CCI, MFI, and CMO meet specific criteria. Note: This is a sample strategy provided as a starting point, and you can customize it by adding more indicators and methods to suit your specific needs.
startup_candle_count : 50 cmo: -15.822%
stoploss: -0.05 timeframe: 15m hash(sha256): 37d4c319b11302f0c27258f003e00600fd1f1bb763cdd3eeead7eb9abe8e2f9e indicators: mfi cci cmo
No similar strategies found. (based on used indicators)
last change: 2023-07-04 04:13:52