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The "JustROCR5" strategy is a trading strategy implemented in Python using the FreqTrade library. It is designed for backtesting purposes on a website. Here is a brief description of what the strategy does:
It calculates two Rate of Change Ratio (ROCR) indicators using the talib library: "rocr" with a time period of 5 and "rocr_2" with a time period of 2.
In the "populate_buy_trend" function, the strategy identifies a buy signal when the "rocr" value is greater than 1.10 and the "rocr_2" value is greater than 1.01.
It marks the corresponding rows in the DataFrame with a "buy" signal.
The "populate_sell_trend" function is empty in the provided code, indicating that the strategy does not define any specific conditions for selling. You would need to add your own logic for determining the sell signals based on your trading strategy. The strategy includes predefined parameters: "minimal_roi" defines the minimum return on investment (ROI) target as 0.05 (5%), "stoploss" sets a stop-loss level at -0.01 (-1%), "trailing_stop" enables trailing stop functionality, and "ticker_interval" sets the interval for ticker data to '1m' (1 minute). This strategy focuses on identifying potential buying opportunities based on the rate of change in the price. You can further customize it by adding sell conditions and adjusting the indicator parameters to fit your specific trading strategy.
In the "populate_buy_trend" function, the strategy identifies a buy signal when the "rocr" value is greater than 1.10 and the "rocr_2" value is greater than 1.01.
It marks the corresponding rows in the DataFrame with a "buy" signal.
The "populate_sell_trend" function is empty in the provided code, indicating that the strategy does not define any specific conditions for selling. You would need to add your own logic for determining the sell signals based on your trading strategy. The strategy includes predefined parameters: "minimal_roi" defines the minimum return on investment (ROI) target as 0.05 (5%), "stoploss" sets a stop-loss level at -0.01 (-1%), "trailing_stop" enables trailing stop functionality, and "ticker_interval" sets the interval for ticker data to '1m' (1 minute). This strategy focuses on identifying potential buying opportunities based on the rate of change in the price. You can further customize it by adding sell conditions and adjusting the indicator parameters to fit your specific trading strategy.
stoploss: -0.01 timeframe: 1m hash(sha256): 39c4be6a37f5c2a8e105dc71f2bfb768736f55cede6be6c2757fef5666050dcc indicators: rocr rocr_2
No similar strategies found. (based on used indicators)
last change: 2023-06-29 03:14:59