以地缘政治风险和商业周期为条件预测美国股票回报率

IF 7.5 1区 经济学 Q1 BUSINESS, FINANCE
Minh Tam Tammy Schlosky , Serkan Karadas , Adam Stivers
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引用次数: 0

摘要

利用预测文献中的标准预测因子,我们预测了 1927-2021 年地缘政治风险和商业周期条件下的美国股市回报率。我们发现,在地缘政治风险高与地缘政治风险低的时期,样本外预测性能明显更好。与之前的研究一致,我们进一步发现了在经济衰退时回报率可预测性提高的证据。然而,一旦地缘政治风险水平得到控制,我们就会发现经济衰退与经济扩张时期的预测性能差别不大。如果用股市周期和工业生产正增长/负增长时期代替经济衰退/经济扩张时期,我们也会发现类似的结果。我们的研究证明地缘政治风险本身以及与商业周期指标相结合会影响文献中标准预测变量的预测能力,从而为预测文献做出了贡献。我们还通过时变回报可预测性的证据为适应性市场假说的文献做出了贡献。至于我们的结果是基于时变可预测性还是时变风险,我们没有找到定论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
CiteScore
10.30
自引率
9.80%
发文量
366
期刊介绍: The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.
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