An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios

Chaibva, Tendayi

An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios

Thesis / Dissertation

2026

Publisher

University of Cape Town

Department

Department of Finance and Tax

Faculty

Faculty of Commerce

Abstract

This study examines the Fama and French Five-Factor (FF5) model's significance, explanatory ability and model fit across 30 United States (U.S.) industry portfolios in the pre- and post-COVID-19 periods. The research investigates whether the pandemic an exogenous global financial shock altered the model's explanatory power and the stability of its factor loadings. Grounded in multifactor asset pricing theory, the study aims to determine whether the relationships between expected returns and the five key risk factors market (MKT), size (SMB), value (HML), profitability (RMW) and investment (CMA) remained consistent or experienced structural change following the pandemic. Using quantitative regression analysis, the research employs Ordinary Least Squares (OLS) techniques to test the FF5 model on both daily and monthly data obtained from the Kenneth R. French Data Library. The analysis compares two distinct periods pre-COVID-19 (January 2017–December 2019) and post-COVID-19 (January 2021–December 2023) while excluding 2020 due to extraordinary market volatility. The model's performance is evaluated based on changes in factor coefficients, p-values, adjusted R² and F-statistics to assess variations in explanatory power and statistical significance. The findings indicate that the Fama and French Five-Factor model retained its overall explanatory power across both periods, with the adjusted R² increasing post-pandemic. The market (MKT) and value (HML) factors remained consistently significant across most industries, while the profitability (RMW) and investment (CMA) factors exhibited improved stability in the post-COVID-19 period, particularly in capital-intensive sectors. The OLS F-statistics also revealed a general rise in model significance, underscoring stronger factor driven relationships after the pandemic. Overall, the results support the null hypothesis (H₀) that there is no significant difference in the FF5 model's explanatory power between the pre- and post-COVID-19 periods. The study concludes that the FF5 model remains a robust and reliable framework for explaining industry-level asset returns, even amid structural economic disruptions. These findings reaffirm the model's theoretical validity and empirical relevance in evolving financial environments, providing valuable insights for both academic research and investment strategy formulation.

Keywords

Fama-French Five-Factor Model, Asset Pricing, COVID-19, Industry Portfolios, Model Fit, Factor Loadings, Financial Markets, Regression Analysis

Reference:

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