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The inadvertent use of information in a historical backtest that was not actually available at the simulated point in time.
The inadvertent use of information in a historical backtest that was not actually available at the simulated point in time.
Look-ahead bias corrupts backtest accuracy by introducing future pricing or fundamental data into past decision nodes.
Common error: Using end-of-day closing prices to calculate signals executed at market open.
Invalidates backtest results, creating artificially inflated performance metrics.
Financial machine learning is the application of supervised, unsupervised, and reinforcement learning methods to financial prediction, classification, and decision problems. The defining methodological constraint is that financial data are serially correlated, not independently and identically distributed, which means that the standard machine learning toolkit must be substantially adapted. The dominant practitioner reference is López de Prado (2018).
Research methodology is the set of practices that distinguish a rigorous quant research process from a hopeful one. The central topics are backtest audit, multiple testing correction, purged and combinatorial cross-validation, walk-forward optimisation, the triple-barrier labelling method, and the deflated Sharpe ratio. The dominant practitioner reference is López de Prado (2018).