Excellent article. One possible solution to many of these issues is the development of adaptive and auditable frameworks that prioritize economic causality and regime interpretation over pure statistical optimization.
Quantitative models become structurally fragile when they rely on static relationships, isolated factors, or excessive historical fitting without considering how volatility, liquidity, correlations, and macro conditions evolve across different market environments.
Frameworks with regime-aware thresholds, multi-signal confirmation, causal filtering, and transparent decision logic may offer a more robust approach to reducing overfitting and improving long-term interpretability under changing market structures.
Excellent article. One possible solution to many of these issues is the development of adaptive and auditable frameworks that prioritize economic causality and regime interpretation over pure statistical optimization.
Quantitative models become structurally fragile when they rely on static relationships, isolated factors, or excessive historical fitting without considering how volatility, liquidity, correlations, and macro conditions evolve across different market environments.
Frameworks with regime-aware thresholds, multi-signal confirmation, causal filtering, and transparent decision logic may offer a more robust approach to reducing overfitting and improving long-term interpretability under changing market structures.