Uses of Package
com.quantfinlib.backtest.validation
Packages that use com.quantfinlib.backtest.validation
Package
Description
The defense against overfit backtests:
ParameterGrid +
GridSearchOptimizer enumerate
and rank parameter combinations;
WalkForwardAnalyzer optimizes
on rolling train windows and evaluates on unseen test windows, stitching
out-of-sample equity (capital carries across folds) and reporting the
walk-forward efficiency ratio;
SharpeValidation applies the
Bailey/López de Prado probabilistic and deflated Sharpe — the
multiple-testing haircut for grid-picked winners — plus the minimum
track record length (how many periods before the record MEANS
something, in closed form);
BlockBootstrap hands the
backtest Sharpe its sampling DISTRIBUTION (stationary Politis-Romano
blocks — an iid resample destroys the autocorrelation and understates
the uncertainty, the classic route to false confidence): the honest
question is whether the 5th percentile is still positive, not whether
1.2 is a good number.-
Classes in com.quantfinlib.backtest.validation used by com.quantfinlib.backtest.validationClassDescriptionA named parameter grid for strategy optimization;
ParameterGrid.combinations()enumerates the cartesian product in deterministic order.One fold: test on[testFrom, testTo), train ontrainIndices(ascending, purged and embargoed).Builds a strategy instance from one parameter combination.