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The "mp" strategy is designed for backtesting trading strategies on a 5-minute candle timeframe. It focuses on identifying potential buy and sell signals based on local minima and maxima of the price data. The strategy aims to capture short-term price movements.
Key Features: Ticker Interval: 5 minutes Sell Signal: Enabled Sell Profit Only: Disabled Ignore ROI on Buy Signal: Disabled Process Only New Candles: Enabled Risk Management: Minimal ROI: Aims for a minimum of 1.0 (break-even) Stoploss: -0.1 (10% stop loss) Trailing Stop: Trailing Stop Enabled: No Trailing Stop Positive: 0.32234 Trailing Stop Positive Offset: 0.40815 Trailing Only Offset Is Reached: No Indicators: The strategy uses the argrelextrema function from SciPy to find local minima and maxima of the closing price.
These points are stored in the min and max columns of the DataFrame, respectively.
Buy Signal: A buy signal is generated when the min column is not null, indicating a local minimum has been detected. The 'buy' column in the DataFrame is set to 1 for these points. Sell Signal: A sell signal is generated when the max column is not null, indicating a local maximum has been detected. The 'sell' column in the DataFrame is set to 1 for these points. Overall, the strategy seeks to capitalize on short-term price fluctuations by buying at local minima and selling at local maxima. It does not employ a trailing stop mechanism but includes a stop loss for risk management.
Key Features: Ticker Interval: 5 minutes Sell Signal: Enabled Sell Profit Only: Disabled Ignore ROI on Buy Signal: Disabled Process Only New Candles: Enabled Risk Management: Minimal ROI: Aims for a minimum of 1.0 (break-even) Stoploss: -0.1 (10% stop loss) Trailing Stop: Trailing Stop Enabled: No Trailing Stop Positive: 0.32234 Trailing Stop Positive Offset: 0.40815 Trailing Only Offset Is Reached: No Indicators: The strategy uses the argrelextrema function from SciPy to find local minima and maxima of the closing price.
These points are stored in the min and max columns of the DataFrame, respectively.
Buy Signal: A buy signal is generated when the min column is not null, indicating a local minimum has been detected. The 'buy' column in the DataFrame is set to 1 for these points. Sell Signal: A sell signal is generated when the max column is not null, indicating a local maximum has been detected. The 'sell' column in the DataFrame is set to 1 for these points. Overall, the strategy seeks to capitalize on short-term price fluctuations by buying at local minima and selling at local maxima. It does not employ a trailing stop mechanism but includes a stop loss for risk management.
startup_candle_count : 50 Recursive Analysis found no issues while using 50 startup_candle_count
Biased Indicators
max, min
stoploss: -0.1 timeframe: 5m hash(sha256): 22b0846ca385ee7f5a8fc49b4eed95800056ff4504327cbcb9bbaaa2b4d6957e indicators: min max close
No similar strategies found. (based on used indicators)
last change: 2023-08-01 07:58:28