Energy Market Uncertainties and US State-Level Stock Market Volatility: A GARCH-MIDAS Approach

Afees Salisu, Ahamuefula Oghonna (), Rangan Gupta and Oguzhan Cepni
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Ahamuefula Oghonna: Centre for Econometrics and Applied Research, Ibadan, Nigeria

No 202409, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we employ the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of state-level stock returns in the United States (US) based on monthly metrics of oil price uncertainty (OPU), and relatively broader energy market-related uncertainty index (EUI). We find that over the daily period of (February) 1994 to (September) 2022 and various forecast horizons, in 37 out of the 50 states, the GARCH-MIDAS model with EUI can outperform the benchmark, i.e., the GARCH-MIDAS-realized volatility (RV), which in turn, holds for at most 18 cases under OPU. The statistical evidence is further strengthened when we are able to detect higher utlilty gains delivered for 42 states by the GARCH-MIDAS-EUI in comparison to the GARCH-MIDAS-RV. Our findings have important implications for investors and policymakers.

Keywords: Monthly Oil Price and Energy Market Uncertainties; Daily State-Level Stock Returns Volatility; GARCH-MIDAS; Forecasting (search for similar items in EconPapers)
JEL-codes: C32 C53 G10 Q02 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2024-03
New Economics Papers: this item is included in nep-ene, nep-for and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202409

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