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The Diamond strategy is a trading strategy implemented in Python for backtesting purposes. It uses various parameters and indicators to determine the buying and selling decisions. Here's a breakdown of how the strategy works:
The strategy defines hyperparameters for buying and selling.
These parameters include the vertical and horizontal push values, as well as the keys for fast and slow indicators used for buying and selling decisions.
It sets the minimal return on investment (ROI) table, which specifies the target returns at different stages of the trade.
A stoploss parameter is defined to limit the maximum loss allowed for a trade. The strategy enables trailing stop, which adjusts the stop price as the trade progresses in a favorable direction. It uses positive offset values to determine when to trail the stop. The timeframe for the strategy is set to 5 minutes. The strategy includes functions to populate indicators, buy trends, and sell trends in the trading dataframe. The populate_indicators function can be used to add additional indicators to the dataframe. In the current implementation, it is commented out, but you can uncomment it and add indicators like moving averages (MA) using the ta library. The populate_buy_trend function populates the 'buy' column in the dataframe based on specific conditions. It checks if the fast indicator crosses above the shifted slow indicator multiplied by the vertical push value. The populate_sell_trend function populates the 'sell' column based on conditions similar to the buy trend but using the crossed below condition. Overall, the Diamond strategy aims to identify buying and selling opportunities based on the crossover of indicators and specific parameter values. The strategy can be further customized by adding more indicators and adjusting the hyperparameters to optimize performance.
These parameters include the vertical and horizontal push values, as well as the keys for fast and slow indicators used for buying and selling decisions.
It sets the minimal return on investment (ROI) table, which specifies the target returns at different stages of the trade.
A stoploss parameter is defined to limit the maximum loss allowed for a trade. The strategy enables trailing stop, which adjusts the stop price as the trade progresses in a favorable direction. It uses positive offset values to determine when to trail the stop. The timeframe for the strategy is set to 5 minutes. The strategy includes functions to populate indicators, buy trends, and sell trends in the trading dataframe. The populate_indicators function can be used to add additional indicators to the dataframe. In the current implementation, it is commented out, but you can uncomment it and add indicators like moving averages (MA) using the ta library. The populate_buy_trend function populates the 'buy' column in the dataframe based on specific conditions. It checks if the fast indicator crosses above the shifted slow indicator multiplied by the vertical push value. The populate_sell_trend function populates the 'sell' column based on conditions similar to the buy trend but using the crossed below condition. Overall, the Diamond strategy aims to identify buying and selling opportunities based on the crossover of indicators and specific parameter values. The strategy can be further customized by adding more indicators and adjusting the hyperparameters to optimize performance.
stoploss: -0.271 timeframe: 5m hash(sha256): 5645da27461eb1d00fcce3251c8381f833d81d98940a42e54816c5c144bd5111
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last change: 2022-07-11 03:05:15