Forecasting U.S. Stock Returns Conditional on Geopolitical Risk and Business Cycles
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. • We forecast the U.S. stock market returns conditional on geopolitical risk and business cycles over the 1927–2021 period. • We demonstrate that geopolitical risk impacts the forecasting ability of standard forecasting variables. • We find little difference in forecasting performance in recessions versus expansions after controlling for geopolitical risk. • We highlight the importance of geopolitical risk in forecasting studies.
Authors
- Minh Tam Tammy Schlosky (ORCID: https://orcid.org/0000-0002-2695-5003)
- Adam Stivers (ORCID: https://orcid.org/0000-0001-6164-2785)
- Serkan Karadas
Institutions
- University of Wisconsin–La Crosse (US)
- University of Illinois at Springfield (US)
Publication Details
- Journal
- International Review of Financial Analysis
- Published
- 2024-10-24
- DOI
- https://doi.org/10.1016/j.irfa.2024.103707
- Citations
- 4
- Primary Topic
- Market Dynamics and Volatility
- Type
- article
- Field-Weighted Citation Impact
- 4.52