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The GodStraNewOpt2 strategy is a backtesting strategy that calculates and optimizes indicators to generate buy and sell signals. The strategy consists of three main components: indicator calculation, buy signal generation, and sell signal generation. In the populate_indicators method, the strategy calculates default values for hyperoptable parameters but doesn't generate any useful data for optimization.
Instead, specific indicators are calculated within the buy and sell signal generation methods if needed.
The populate_buy_trend method populates the buy signals.
It starts by defining a list of conditions. Each condition is generated using the condition_generator function, which takes in parameters such as buy operators, indicators, crossed indicators, and real numbers. The generated conditions are appended to the list. This process is repeated three times with different sets of indicators. Finally, if there are any conditions present, the strategy sets the 'buy' column to 1 for rows where all the conditions are met. Similarly, the populate_sell_trend method populates the sell signals. It follows the same process as the buy signal generation but with sell-specific indicators and parameters. The generated conditions are appended to a list, and if any conditions exist, the strategy sets the 'sell' column to 1 for rows where all the conditions are met. Overall, the strategy calculates indicators, generates buy and sell signals based on specific conditions, and assigns corresponding values in the 'buy' and 'sell' columns of the DataFrame.
Instead, specific indicators are calculated within the buy and sell signal generation methods if needed.
The populate_buy_trend method populates the buy signals.
It starts by defining a list of conditions. Each condition is generated using the condition_generator function, which takes in parameters such as buy operators, indicators, crossed indicators, and real numbers. The generated conditions are appended to the list. This process is repeated three times with different sets of indicators. Finally, if there are any conditions present, the strategy sets the 'buy' column to 1 for rows where all the conditions are met. Similarly, the populate_sell_trend method populates the sell signals. It follows the same process as the buy signal generation but with sell-specific indicators and parameters. The generated conditions are appended to a list, and if any conditions exist, the strategy sets the 'sell' column to 1 for rows where all the conditions are met. Overall, the strategy calculates indicators, generates buy and sell signals based on specific conditions, and assigns corresponding values in the 'buy' and 'sell' columns of the DataFrame.
stoploss: -0.97 timeframe: 5m hash(sha256): 903d313d9be80712ccb0ed337bb7a7da1cda9e6a90ce7523dbe26cad3213de5c indicators: volume indicator_trend_sma crossed_indicator indicator sharp_indicator
No similar strategies found. (based on used indicators)
last change: 2024-04-28 14:32:30