The "CustomStrategy" is a trading strategy implemented in Python for backtesting purposes. It is designed to generate buy and sell signals based on technical indicators. Here is a breakdown of what the strategy does:
Indicators:
ADX (Average Directional Index): Calculates the strength of a trend.
CCI (Commodity Channel Index): Identifies overbought and oversold conditions.
Stoch (Stochastic Oscillator): Measures the current price relative to its price range over a given period.
Slow Stoch: Similar to Stoch, but with a longer period. EMA (Exponential Moving Average): Smooths out price data to identify trends. Buy Signal: The strategy generates a buy signal when the following conditions are met: ADX is greater than 50 or slow ADX is greater than 26. CCI is less than -100. Fast %K and %D (from Stoch) in the previous period are both below 20. Slow Fast %K and %D (from Slow Stoch) in the previous period are both below 30. Fast %K in the current period is greater than %D. Mean volume is greater than 0.75. Close price is greater than 0.00000100. Sell Signal: The strategy generates a sell signal when the following conditions are met: Slow ADX is less than 25. Fast %K or %D (from Stoch) in the current period is greater than 70. Fast %K in the current period is greater than %D. Close price is greater than the EMA with a time period of 5. The strategy aims to achieve a minimal return on investment (ROI) as defined in the minimal_roi variable. The stop-loss is set to -0.3, indicating a maximum acceptable loss. The ticker interval for analyzing price data is set to 5. Please note that this description provides a high-level overview of the strategy's functionality. For a more detailed understanding, it is recommended to review the code and consult the author's GitHub repository for additional information.
CCI (Commodity Channel Index): Identifies overbought and oversold conditions.
Stoch (Stochastic Oscillator): Measures the current price relative to its price range over a given period.
Slow Stoch: Similar to Stoch, but with a longer period. EMA (Exponential Moving Average): Smooths out price data to identify trends. Buy Signal: The strategy generates a buy signal when the following conditions are met: ADX is greater than 50 or slow ADX is greater than 26. CCI is less than -100. Fast %K and %D (from Stoch) in the previous period are both below 20. Slow Fast %K and %D (from Slow Stoch) in the previous period are both below 30. Fast %K in the current period is greater than %D. Mean volume is greater than 0.75. Close price is greater than 0.00000100. Sell Signal: The strategy generates a sell signal when the following conditions are met: Slow ADX is less than 25. Fast %K or %D (from Stoch) in the current period is greater than 70. Fast %K in the current period is greater than %D. Close price is greater than the EMA with a time period of 5. The strategy aims to achieve a minimal return on investment (ROI) as defined in the minimal_roi variable. The stop-loss is set to -0.3, indicating a maximum acceptable loss. The ticker interval for analyzing price data is set to 5. Please note that this description provides a high-level overview of the strategy's functionality. For a more detailed understanding, it is recommended to review the code and consult the author's GitHub repository for additional information.
stoploss: -0.3 timeframe: 5m hash(sha256): 070c21113323a2d488216aff472e3663a3e858d44dceffdaa63f17edb85af5ef indicators: meanvolume slowfastkprevious slowfastdprevious adx slowfastd volume slowadx close cci fastkprevious ema5 fastd fastk slowfastk fastdprevious
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last change: 2024-04-27 23:38:38