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The CMCWinner strategy is designed for backtesting trading strategies on a website. It uses various technical indicators to generate buy and sell signals based on specific conditions. Here's a breakdown of what the strategy does:
The strategy uses the following technical indicators: Commodity Channel Index (CCI), Money Flow Index (MFI), and Chande Momentum Oscillator (CMO).
The populate_indicators method adds these indicators to the input DataFrame.
The populate_buy_trend method generates buy signals based on the following conditions: CCI value from the previous time step is less than -100.
MFI value from the previous time step is less than 20. CMO value from the previous time step is less than -50. If these conditions are met, the 'buy' column in the DataFrame is set to 1. The populate_sell_trend method generates sell signals based on the following conditions: CCI value from the previous time step is greater than 100. MFI value from the previous time step is greater than 80. CMO value from the previous time step is greater than 50. If these conditions are met, the 'sell' column in the DataFrame is set to 1. Additionally, the strategy defines the following attributes: minimal_roi: A dictionary defining the minimal return on investment (ROI) for different time periods. It specifies the desired ROI at different stages of the trade. For example, a ROI of 0% at 40% of the trade duration, 2% at 30%, 3% at 20%, and 5% at the end (0% duration). stoploss: The optimal stop-loss value for the strategy, expressed as a percentage. If the trade goes against the expected direction and reaches this stop-loss value, the position is closed. timeframe: The optimal timeframe for the strategy, indicating the duration of each candlestick in the data used for analysis (e.g., 15 minutes). Please note that this is a sample strategy, and you can customize it by adding or modifying methods and indicators according to your requirements.
The populate_indicators method adds these indicators to the input DataFrame.
The populate_buy_trend method generates buy signals based on the following conditions: CCI value from the previous time step is less than -100.
MFI value from the previous time step is less than 20. CMO value from the previous time step is less than -50. If these conditions are met, the 'buy' column in the DataFrame is set to 1. The populate_sell_trend method generates sell signals based on the following conditions: CCI value from the previous time step is greater than 100. MFI value from the previous time step is greater than 80. CMO value from the previous time step is greater than 50. If these conditions are met, the 'sell' column in the DataFrame is set to 1. Additionally, the strategy defines the following attributes: minimal_roi: A dictionary defining the minimal return on investment (ROI) for different time periods. It specifies the desired ROI at different stages of the trade. For example, a ROI of 0% at 40% of the trade duration, 2% at 30%, 3% at 20%, and 5% at the end (0% duration). stoploss: The optimal stop-loss value for the strategy, expressed as a percentage. If the trade goes against the expected direction and reaches this stop-loss value, the position is closed. timeframe: The optimal timeframe for the strategy, indicating the duration of each candlestick in the data used for analysis (e.g., 15 minutes). Please note that this is a sample strategy, and you can customize it by adding or modifying methods and indicators according to your requirements.
startup_candle_count : 50 cmo: -15.822%
stoploss: -0.05 timeframe: 15m hash(sha256): 3cf873558c07dc8a5fbf9c9fdf59d0ead8dc4da6ea649f8060a1194b199180cc indicators: mfi cci cmo
No similar strategies found. (based on used indicators)
last change: 2023-09-23 04:46:32