Price Conflict and US Stock Return Volatility Forecasting: Insights from over 150 Years with a Mixed-Frequency Framework

Afees Salisu, Ahamuefula Ogbonna, Rangan Gupta () and Elie Bouri ()
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Afees Salisu: Centre for Econometrics and Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa
Ahamuefula Ogbonna: Centre for Econometrics and Applied Research, Ibadan, Nigeria
Rangan Gupta: Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa
Elie Bouri: School of Business, Lebanese American University, Lebanon

No 202620, Working Papers from University of Pretoria, Department of Economics

Abstract: This paper employs the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast monthly and daily stock return volatility in the United States (US), based on a quarterly news-based Price Conflict Index (PCI) that signals “bad macroeconomic news†. An analysis of historical monthly (1860-2023) and daily (1885-2023) data demonstrates that the GARCH-MIDAS model incorporating PCI outperforms both the benchmark GARCH-MIDAS model with realized volatility (GARCH-MIDAS-RV) and models with macroeconomic variables such as output growth, inflation, unemployment, and interest rates. Furthermore, the inclusion of the PCI in modeling stock return volatility provides higher utility gains compared to models that exclude it. These findings have important implications for both investors and policymakers.

Keywords: Price Conflict; Stock Returns Volatility; Forecasting; GARCH-MIDAS (search for similar items in EconPapers)
JEL-codes: C32 C53 E31 G12 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2026-08
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