Forecasting U.S. Stock Returns Conditional on Geopolitical Risk and Business Cycles

Minh Tam Tammy Schlosky, Serkan Karadas and Adam Stivers

International Review of Financial Analysis, 2024, vol. 96, issue PB

Abstract: Using standard predictors in the forecasting literature, we forecast the U.S. stock market returns conditional on geopolitical risk and business cycles over the 1927–2021 period. We find that out-of-sample forecasting performance is significantly better in times of high geopolitical risk versus low geopolitical risk. Consistent with previous research, we find further evidence of improved return predictability in recessions. However, we find little difference in forecasting performance in recessions versus expansions once the level of geopolitical risk is controlled for. We find similar results when using stock market cycles and periods of positive/negative industrial production growth in place of recessions/expansions. Our study contributes to the forecasting literature by documenting that geopolitical risk by itself and in combination with business cycle indicators impacts the forecasting ability of standard forecasting variables in the literature. We also contribute to the literature on the adaptive markets hypothesis with evidence of time-varying return predictability. We find inconclusive evidence as to whether our results are based on time-varying predictability or time-varying risk.

Keywords: Forecasting; Return predictability; Geopolitical risk; Business cycles (search for similar items in EconPapers)
JEL-codes: C58 F51 F52 G14 G17 G41 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:96:y:2024:i:pb:s1057521924006392

DOI: 10.1016/j.irfa.2024.103707

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