Model Robustness Metrics

Model robustness metrics are quantitative measures used to determine if a trading strategy maintains its performance characteristics across various market conditions and parameter changes. These metrics help identify if a strategy is fragile or if it can adapt to shifts in market volatility, liquidity, or trends.

By stress-testing the model with different parameter settings, researchers can observe how sensitive the performance is to minor changes. A robust model should show consistent performance without requiring extreme optimization.

In crypto, where volatility is extreme, robustness metrics like the Sharpe ratio, Calmar ratio, and maximum drawdown are essential for assessing whether a strategy's success is due to a genuine edge or merely favorable market conditions.