Beyond Volatility: A Leakage-Safe Residual-Stress Signal for Drawdown Risk Monitoring

Monitoring equity drawdown risk requires real-time indicators that can be implemented without look-ahead bias and that may add information beyond standard volatility measures. This study develops a leakage-safe residual-stress indicator from cross-sectional PCA reconstruction errors in U.S. sector excess returns and examines whether it contributes to drawdown-risk monitoring. Using daily adjusted prices for SPY and 11 U.S. sector ETFs over 2020–2025, this study computes sector excess returns relative to SPY, estimate the common component with principal component analysis (PCA), and define residual stress as the cross-sectional root-mean-square magnitude of out-of-sample reconstruction residuals. The PCA mapping is estimated using information available only through t − 1, stress is computed at t, and high-stress regimes are defined using rolling train-only quantile thresholds shifted forward by one trading day. Performance is evaluated using drawdown- onset events and early-warning metrics including ROC-AUC, PR-AUC, and horizon-H precision and recall. The results indicate that although residual stress is not a superior standalone alternative to realized volatility, it remains the stronger benchmark in overall classification performance. Residual stress is most useful as a complementary indicator of cross-sectional market dislocation rather than as a replacement for volatility. In the baseline sample, residual-stress spikes cluster around drawdown onsets, and conditional regime analysis shows that when volatility is low, high residual stress is associated with a materially higher probability of a drawdown onset within the next H = 21 trading days than the low-stress/low-volatility regime. Event-overlap and lead-time diagnostics further suggest that residual stress can flag a subset of onset episodes not captured by a simple volatility- threshold rule, although its primary incremental value lies in conditional risk stratification rather than in systematically earlier triggering. A longer-history proxy-sector analysis yields similar evidence of conditional complementarity while also confirming the stronger standalone performance of volatility. The paper’s contribution is to develop a leakage- safe, interpretable, cross-sectional residual-stress diagnostic that improves conditional drawdown-risk stratification, especially in otherwise low-volatility states, rather than a standalone replacement for realized volatility. This interpretation is supported by both a modern ETF baseline sample and a longer-history proxy-sector sample, with the broader sample providing more stable evidence of complementarity across a larger set of drawdown onsets