¿Qué es Label overlap, purging, embargo, combinatorial purged cross-validation?

Label overlap occurs when the targets of different observations share periods, as $h$-day forward returns observed every day do. Purging removes from the training set every observation whose label overlaps in time the labels of the test set; an embargo also removes the training observations that immediately follow the test set, since features are serially correlated. Combinatorial purged cross-validation (CPCV) uses every choice of $k$ test folds out of $n$, purged and embargoed, recombining the test folds into $\binom{n}{k}k/n$ backtest paths (López de Prado, 2018; as implemented in open-source libraries such as skfolio).