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Purged and Embargoed Cross-Validation is a time-series-aware model validation technique designed to address information leakage in financial machine learning. It is especially applicable when labels span time intervals rather than individual points in time. The method modifies standard k-fold cross-validation by incorporating two critical mechanisms: purging and embargoing.
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