Oil versus Non-Oil Geopolitical Risk and US Industry Stock Market Volatility

This study examines whether decomposing the geopolitical risk (GPR) index into oil- and non-oil-related components yields incremental explanatory power for U.S. industry stock market volatility. Using daily conditional volatilities derived from a GJR-GARCH model with time-varying skewness and kurtosis (GJR-SK) across 49 Fama-French industries, we estimate autoregressive specifications with exogenous inputs (ARX). Each model incorporates rich macro-financial controls, including market portfolio volatility, the Aruoba-Diebold-Scotti business conditions index, and the shadow-rate-augmented federal funds rate. Through a sequence of properly nested F-tests, we address three core empirical questions: (i) whether non-oil GPR adds predictive content beyond the macro baseline; (ii) whether oil-specific GPR provides incremental information once non-oil GPR is controlled for; and (iii) whether a geographic decomposition across eight oil-producing regions enhances explanatory power beyond aggregate metrics. We find that non-oil GPR is incrementally significant in 35 of 49 industries. Conditional on non-oil GPR, aggregate oil-related risk remains incrementally significant in 23 industries, while its regional breakdown increases significance to 29 industries. Estimated coefficients demonstrate marked sign heterogeneity: for oil-intensive sectors, non-oil GPR reduces volatility while oil-specific risk elevates it, supporting a commodity-price information-resolution channel; for non-oil-intensive sectors, the pattern reverses, consistent with the classical risk-aversion channel of Bloom (2009). Regionally, geopolitical risk originating in the Middle East, Venezuela, and Asia systematically amplifies industry volatility, whereas risk originating in Russia and Africa exerts a stabilizing, volatility-dampening effect.