assay_pbo

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Use this when you have the T x N returns of a grid search and want the probability of backtest overfitting (PBO, CSCV) -- did the sweep find an edge or manufacture one? A demote-only audit, not buy/sell advice. Did your parameter sweep FIND an edge -- or manufacture one? PBO over the whole trial matrix. Submit the full T x N payoff matrix of every configuration you tried (rows = time-ordered per-period returns, columns = the candidates from your grid search / parameter sweep / optimisation run) and get the Probability of Backtest Overfitting via combinatorial symmetric cross-validation (CSCV, Bailey/Borwein/Lopez de Prado/Zhu 2017) with purge and embargo against overlapping-label leakage: the fraction of train/test splits in which your in-sample winner ranks at or below the out-of-sample median. The dossier adds the performance-degradation slope (does out-of-sample decay as in-sample shines?), the probability of out-of-sample loss, and first-order stochastic dominance of your selected picks versus the whole pool. Complements the trial ledger: the ledger counts how many tries your family burned, PBO grades whether the SELECTION PROCESS itself is overfit -- PBO >= 0.5 earns the named demote PBO_HIGH. Exhaustive enumeration with nothing to seed, fail-closed on undersized, oversized or non-numeric input. Demote-only: it can kill a selection, never bless one. NOT a buy/sell signal. Price: per check; see https://api.alphaassay.com/v1/meta/pricing (api_key required -- account setup at https://api.alphaassay.com/account).