From 18305a5bf6b163b6d7609ee4ff953f9a3b2dfcce Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 3 Dec 2024 19:16:48 +0100 Subject: [PATCH] docs: update hyperopt docs to include new argument --- docs/advanced-hyperopt.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md index 480b20daf..b12d8f5b6 100644 --- a/docs/advanced-hyperopt.md +++ b/docs/advanced-hyperopt.md @@ -39,6 +39,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss): config: Config, processed: dict[str, DataFrame], backtest_stats: dict[str, Any], + starting_balance: float, **kwargs, ) -> 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). * `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`. +* `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.