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

Afees A. Salisu, Ahamuefula E. Ogbonna, Rangan Gupta, Oguzhan Cepni

Research output: Working paperResearch

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.
Original languageEnglish
Place of PublicationPretoria
PublisherUniversity of Pretoria
Number of pages22
Publication statusPublished - Mar 2024
SeriesWorking Paper Series / Department of Economics. University of Pretoria
Number2024-09

Keywords

  • Monthly oil price and energy market uncertainties
  • Daily state-level stock returns volatility
  • GARCH-MIDAS
  • Forecasting

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