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The EMAStrategy is a simple trading strategy implemented in Python for backtesting purposes. It is designed to generate buy and sell signals based on the crossover of two exponential moving averages (EMAs). Here's a breakdown of the strategy:
Minimal ROI: The strategy has a predefined minimal return on investment (ROI) of 0.5, which means it aims to achieve a 0.5% profit on each trade.
This value can be adjusted in the configuration file.
Stoploss: The strategy has a predefined optimal stoploss of -0.2, which means it will trigger a sell signal if the trade goes against the expected direction by 0.2%.
This value can also be adjusted in the configuration file. Ticker interval: The strategy is designed to work with 4-hour candlestick data, meaning it analyzes price movements and generates signals based on 4-hour intervals. Indicator calculation: The strategy calculates two EMAs: a shorter EMA with a time period of 8, and a medium EMA with a time period of 21. These indicators are calculated using the talib library. Buy signal generation: The buy signal is generated when the shorter EMA crosses above the medium EMA. This is checked using the qtpylib.crossed_above function, which returns True when the crossover condition is met. Sell signal generation: The sell signal is generated when the medium EMA crosses above the shorter EMA. Again, the qtpylib.crossed_above function is used to check for the crossover condition. The strategy is described as a proof of concept and is not expected to perform well in actual trading. It serves as an example to showcase the implementation of a basic crossover strategy using EMAs.
This value can be adjusted in the configuration file.
Stoploss: The strategy has a predefined optimal stoploss of -0.2, which means it will trigger a sell signal if the trade goes against the expected direction by 0.2%.
This value can also be adjusted in the configuration file. Ticker interval: The strategy is designed to work with 4-hour candlestick data, meaning it analyzes price movements and generates signals based on 4-hour intervals. Indicator calculation: The strategy calculates two EMAs: a shorter EMA with a time period of 8, and a medium EMA with a time period of 21. These indicators are calculated using the talib library. Buy signal generation: The buy signal is generated when the shorter EMA crosses above the medium EMA. This is checked using the qtpylib.crossed_above function, which returns True when the crossover condition is met. Sell signal generation: The sell signal is generated when the medium EMA crosses above the shorter EMA. Again, the qtpylib.crossed_above function is used to check for the crossover condition. The strategy is described as a proof of concept and is not expected to perform well in actual trading. It serves as an example to showcase the implementation of a basic crossover strategy using EMAs.
stoploss: -0.2 timeframe: 4h hash(sha256): 24a63cf81e4262b18b89f1b533736c1123ec43bd06dd172d2072210adb4a13dd
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last change: 2022-07-02 19:54:08