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The "BuyOrDie" strategy is a trading strategy implemented in Python for backtesting purposes. Here is a short description of what the strategy does:
The strategy uses the "hull_moving_average" indicator from the qtpylib library to calculate a Hull Moving Average with a window of 20 periods. It also creates additional columns in the dataframe to store previous and current values of the closing price and the Hull Moving Average.
In the populate_buy_trend function, the strategy identifies buying opportunities based on the following conditions: The current closing price is higher than the current Hull Moving Average.
The previous closing price is lower than the previous Hull Moving Average.
When these conditions are met, the strategy sets a 'buy' signal of 1 for the corresponding row in the dataframe. The populate_sell_trend function does not implement any selling logic, indicating that the strategy does not specify when to sell. Additionally, the strategy defines various parameters such as buy and sell hyperspace params, a minimal return on investment (ROI) table, a stop-loss percentage, and trailing stop parameters. These parameters can be customized to optimize the strategy's performance. The strategy operates on a 5-minute timeframe and does not use an exit signal or consider ROI if an entry signal is present.
In the populate_buy_trend function, the strategy identifies buying opportunities based on the following conditions: The current closing price is higher than the current Hull Moving Average.
The previous closing price is lower than the previous Hull Moving Average.
When these conditions are met, the strategy sets a 'buy' signal of 1 for the corresponding row in the dataframe. The populate_sell_trend function does not implement any selling logic, indicating that the strategy does not specify when to sell. Additionally, the strategy defines various parameters such as buy and sell hyperspace params, a minimal return on investment (ROI) table, a stop-loss percentage, and trailing stop parameters. These parameters can be customized to optimize the strategy's performance. The strategy operates on a 5-minute timeframe and does not use an exit signal or consider ROI if an entry signal is present.
stoploss: -0.02 timeframe: 5m hash(sha256): da343cda738b2365033d2a78c36e03bdadf645d5d7436e36c1ff021b938e6728
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last change: 2023-06-29 17:55:32