The TestStrategyLegacy is a sample trading strategy for backtesting. It uses various technical analysis (TA) indicators to generate buy and sell signals based on the given DataFrame of market data. The strategy calculates two TA indicators:
ADX (Average Directional Index): It measures the strength of a trend in the market.
TEMA (Triple Exponential Moving Average): It is a moving average that gives more weight to recent price data.
The populate_buy_trend function populates the "buy" column in the DataFrame when the following conditions are met: ADX value is greater than 30, indicating a strong trend.
TEMA value is higher than its previous value, suggesting an upward trend. Volume is greater than 0, ensuring there is trading activity. The populate_sell_trend function populates the "sell" column in the DataFrame when the following conditions are met: ADX value is greater than 70, indicating a very strong trend. TEMA value is lower than its previous value, suggesting a downward trend. Volume is greater than 0, ensuring there is trading activity. The strategy also defines other parameters: minimal_roi: It specifies the desired return on investment (ROI) for the strategy at different stages of profit. For example, when the profit reaches 40%, the strategy aims for a 0% ROI, and when the profit reaches 30%, the strategy aims for a 1% ROI. stoploss: It sets the maximum tolerable loss (as a negative value) before triggering a stop-loss. ticker_interval: It defines the time interval of the market data used for the strategy (e.g., 5 minutes). Please note that this strategy is using legacy function headers, which may be removed in future updates. For an up-to-date version and a template, refer to the sample_strategy.py file in the user_data/strategy directory.
TEMA (Triple Exponential Moving Average): It is a moving average that gives more weight to recent price data.
The populate_buy_trend function populates the "buy" column in the DataFrame when the following conditions are met: ADX value is greater than 30, indicating a strong trend.
TEMA value is higher than its previous value, suggesting an upward trend. Volume is greater than 0, ensuring there is trading activity. The populate_sell_trend function populates the "sell" column in the DataFrame when the following conditions are met: ADX value is greater than 70, indicating a very strong trend. TEMA value is lower than its previous value, suggesting a downward trend. Volume is greater than 0, ensuring there is trading activity. The strategy also defines other parameters: minimal_roi: It specifies the desired return on investment (ROI) for the strategy at different stages of profit. For example, when the profit reaches 40%, the strategy aims for a 0% ROI, and when the profit reaches 30%, the strategy aims for a 1% ROI. stoploss: It sets the maximum tolerable loss (as a negative value) before triggering a stop-loss. ticker_interval: It defines the time interval of the market data used for the strategy (e.g., 5 minutes). Please note that this strategy is using legacy function headers, which may be removed in future updates. For an up-to-date version and a template, refer to the sample_strategy.py file in the user_data/strategy directory.
stoploss: -0.1 timeframe: 5m hash(sha256): 701f3f078af08781114e243550cf7563abff7142a6cef91e957a1fe6b6b1bc3f indicators: volume adx tema
No similar strategies found. (based on used indicators)
last change: 2024-04-28 14:48:37