Financial Risk Disclosure Return Premium: A Topic Modeling Approach

Beichen Zhang, Steve Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We examine the risk factors disclosed in the 10-K financial statement section 1A across 9 years with over 500 hundred companies. We propose a financial disclosure risk factor to extend the Fama-French 3 factor model and Fama-MacBeth cross-section regression. Using the risk factors data from 2015 to 2023, we find the average risk-return premium across nine sectors is significant after controlling for other risk factors from the Fama-French 3-factor model. The premium is measured by monthly return series on risky-minus-less risky stocks or by the coefficient of stock risk factor estimated from cross-section Fama-MacBeth regressions. These text risk factors can potentially be used to construct portfolios that can generate significant returns across different sectors.

Original languageEnglish
Title of host publication2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, CIFEr 2024
ISBN (Electronic)9798350354836
DOIs
StatePublished - 2024
Event2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, CIFEr 2024 - Hoboken, United States
Duration: 22 Oct 202423 Oct 2024

Publication series

Name2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, CIFEr 2024

Conference

Conference2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, CIFEr 2024
Country/TerritoryUnited States
CityHoboken
Period22/10/2423/10/24

Keywords

  • Fama-French 3 factor model
  • Fama-McBeth cross-section regression
  • financial statement
  • risk factors

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