Robustness

There's a persistent risk of overfitting when you optimize strategies on historical data; to protect your capital you should run simple, repeatable robustness tests such as out-of-sample validation, walk-forward testing, parameter-sensitivity scans and randomization checks to expose data snooping and curve-fitting, ensuring your edge survives live markets. Most traders unknowingly optimize to noise, so you must run simple, repeatable checks that reveal fragility and preserve your real performance: out-of-sample testing and walk-forward analysis, parameter sensitivity and Monte Carlo to expose dangerous overfitting, and scenario/stress tests to confirm a robust, tradable edge you can trust in live markets.Understanding Overfitting What is…