{"title":"Stock returns and macroeconomic uncertainty","authors":"Leonardo Iania , P. Thao Nguyen , Kristien Smedts","doi":"10.1016/j.irfa.2025.104263","DOIUrl":null,"url":null,"abstract":"<div><div>This paper provides a comprehensive review of various measures of uncertainty and their asset pricing implications in the cross-section of U.S. stock returns. With a focus on survey-based uncertainty, we add to the list of uncertainty measures previously studied in the literature with novel measures of forecast disagreement sourced from three professional forecast datasets. Through portfolio analyses and stock-level cross-sectional regressions over the sample period between 1989 and 2020, we observe that exposure to uncertainty can explain a significant portion of the cross-sectional dispersion in future stock returns. For survey-based uncertainty, the negative relation between uncertainty and future returns persists over long-term investment horizons, extending up to 36 months, and cannot be explained by the well-established return-predicting factors. Our subsample analysis also reveals that for the uncertainty measures heavily dependent on macroeconomic data, the return predictive power of uncertainty is significantly more prominent in the later subperiod.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"104 ","pages":"Article 104263"},"PeriodicalIF":7.5000,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Financial Analysis","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1057521925003503","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper provides a comprehensive review of various measures of uncertainty and their asset pricing implications in the cross-section of U.S. stock returns. With a focus on survey-based uncertainty, we add to the list of uncertainty measures previously studied in the literature with novel measures of forecast disagreement sourced from three professional forecast datasets. Through portfolio analyses and stock-level cross-sectional regressions over the sample period between 1989 and 2020, we observe that exposure to uncertainty can explain a significant portion of the cross-sectional dispersion in future stock returns. For survey-based uncertainty, the negative relation between uncertainty and future returns persists over long-term investment horizons, extending up to 36 months, and cannot be explained by the well-established return-predicting factors. Our subsample analysis also reveals that for the uncertainty measures heavily dependent on macroeconomic data, the return predictive power of uncertainty is significantly more prominent in the later subperiod.
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.