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docs: update hyperopt docs to include new argument

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Matthias
2024-12-03 19:16:48 +01:00
parent b0b73bf166
commit 18305a5bf6
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docs/advanced-hyperopt.md
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@@ -39,6 +39,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
config: Config, config: Config,
processed: dict[str, DataFrame], processed: dict[str, DataFrame],
backtest_stats: dict[str, Any], backtest_stats: dict[str, Any],
starting_balance: float,
**kwargs, **kwargs,
) -> float: ) -> float:
""" """
@@ -70,6 +71,7 @@ Currently, the arguments are:
* `config`: Config object used (Note: Not all strategy-related parameters will be updated here if they are part of a hyperopt space). * `config`: Config object used (Note: Not all strategy-related parameters will be updated here if they are part of a hyperopt space).
* `processed`: Dict of Dataframes with the pair as keys containing the data used for backtesting. * `processed`: Dict of Dataframes with the pair as keys containing the data used for backtesting.
* `backtest_stats`: Backtesting statistics using the same format as the backtesting file "strategy" substructure. Available fields can be seen in `generate_strategy_stats()` in `optimize_reports.py`. * `backtest_stats`: Backtesting statistics using the same format as the backtesting file "strategy" substructure. Available fields can be seen in `generate_strategy_stats()` in `optimize_reports.py`.
* `starting_balance`: Starting balance used for backtesting.
This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you. This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you.