Uses of Record Class
com.quantfinlib.backtest.validation.GridSearchOptimizer.Candidate

Packages that use GridSearchOptimizer.Candidate

Package

Description

com.quantfinlib.backtest.validation

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.

Uses of GridSearchOptimizer.Candidate in com.quantfinlib.backtest.validation

Methods in com.quantfinlib.backtest.validation that return GridSearchOptimizer.Candidate

Modifier and Type	Method	Description
static GridSearchOptimizer.Candidate	GridSearchOptimizer.best(ParameterGrid grid, StrategyFactory factory, BarSeries series, BacktestConfig config, ToDoubleFunction<PerformanceMetrics> objective)	The winning parameter set only.

Methods in com.quantfinlib.backtest.validation that return types with arguments of type GridSearchOptimizer.Candidate

Modifier and Type	Method	Description
static List<GridSearchOptimizer.Candidate>	GridSearchOptimizer.search(ParameterGrid grid, StrategyFactory factory, BarSeries series, BacktestConfig config, ToDoubleFunction<PerformanceMetrics> objective)

Method parameters in com.quantfinlib.backtest.validation with type arguments of type GridSearchOptimizer.Candidate

Modifier and Type	Method	Description
static double	GridSearchOptimizer.deflatedSharpeOfWinner(List<GridSearchOptimizer.Candidate> ranked, double[] winnerReturns, int periodsPerYear)	The MULTIPLE-TESTING HAIRCUT for the grid's winner: the probability that the top-ranked candidate's Sharpe beats what the best of ranked.size() zero-skill trials would have scored anyway (SharpeValidation.deflatedSharpe(double, double[], int, double, double)).