Quantile-frequency dependence between US sector stock indices and macro-financial indicators: A quantile coherence approach

Abstract

This study explores the quantile-frequency linkages between U.S. sectoral stock indices and four macro-financial indicators: market volatility (VIX), geopolitical risk (GPR), inflation expectations (T5YIE), and the yield curve (T10Y3M), using the Quantile Coherence (QC) framework. The method captures nonlinear and asymmetric interactions across quantiles and horizons. The dataset covers daily observations from January 2016 to July 2025, encompassing episodes such as Brexit, the China-U.S. trade war, and recent geopolitical conflicts. Results reveal strong sectoral heterogeneity: dependence on VIX is predominantly negative in the short term during bullish phases, with reversals at longer horizons; the influence of GPR is asymmetric and forwardlooking; inflation expectations, captured by T5YIE, show a stable long-run positive association with all sectors; while the yield curve (T10Y3M) generates systematic long-term co-movements, with leadership alternating between financial indicators and sector indices across regimes. These findings demonstrate uneven sectoral responses to macro-financial drivers and provide guidance for risk management and portfolio design in uncertain environments