Econometrics
Econometrics provides the foundational tools for understanding financial time series: unit root tests, cointegration analysis, GARCH volatility modeling, and regime detection. I write about applying these methods with proper statistical discipline, because getting the diagnostics wrong means building strategies on unstable ground. These articles assume you can code and want to understand the math behind the models.
Bootstrap Methods for Strategy Robustness: Resampling When You Can't Get More Data
You have one history of market data. Your strategy was designed on that history. How do you estimate performance on data you haven’t seen? Bootstrap resampling generates synthetic histories that …
Walk-Forward Optimization: Anchored vs. Rolling Windows and When Each Fails
Walk-forward validation is the backbone of out-of-sample testing for trading strategies. But the choice of window type, window length, and step size introduces meta-parameters that can themselves be …
Autocorrelation and What It Means for Your Backtest P&L
Autocorrelated returns inflate Sharpe ratios, invalidate standard significance tests, and make backtests look better than reality. This article explains why strategy returns are almost always …
Stationarity Testing for Strategy Signals: ADF, KPSS, and Why Your Backtest Depends on It
A strategy built on a non-stationary signal is a strategy built on sand. This article covers the statistical tests that detect non-stationarity (ADF, KPSS, Phillips-Perron, Zivot-Andrews), explains …