Supply Chain Stress and Industrial Metal Volatility: A GJR-GARCH-MIDAS Approach with Geopolitical Risk Conditioning
Volatility & Financial Econometrics →Abstract
This paper investigates whether global supply chain pressure exerts a measurable influence on the long-run volatility of industrial metal futures, and whether this influence is conditional on the geopolitical environment. Using a GJR-GARCH-MIDAS framework applied to copper and nickel LME front-month futures over January 2005–June 2026, I decompose conditional variance into a short-run asymmetric GARCH component and a long-run component driven by the New York Fed’s Global Supply Chain Pressure Index (GSCPI). The MIDAS slope coefficient is positive and significant for both metals (copper θ = 0.149, p ≈ 0.06; nickel θ = 0.109, p = 0.013), indicating that supply chain stress raises the long-run volatility baseline. Splitting the sample by geopolitical risk (GPR) terciles reveals that copper’s GSCPI sensitivity is concentrated almost entirely in high-GPR regimes (Δθ = +0.249), while nickel retains a smaller but significant effect even in calm periods (Δθ = +0.116). Nickel further displays an anomalous positive leverage coefficient, consistent with the 2022 LME short-squeeze episode. This is the first study to use the GSCPI as a MIDAS long-run driver for industrial metals, and the first to condition that relationship on geopolitical risk.
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Yang, F. (2026). Supply Chain Stress and Industrial Metal Volatility: A GJR-GARCH-MIDAS Approach with Geopolitical Risk Conditioning. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7109258
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