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An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios
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 m...
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| Format: | Thesis |
| Language: | English English |
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Department of Finance and Tax
2026
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| _version_ | 1869483640798314496 |
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| access_status_str | Open Access |
| author | Chaibva, Tendayi |
| author2 | Chun-Sung, Huang |
| author_browse | Chaibva, Tendayi Chun-Sung, Huang |
| author_facet | Chun-Sung, Huang Chaibva, Tendayi |
| author_sort | Chaibva, Tendayi |
| collection | Thesis |
| description | 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. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/43318 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-07-01T04:02:13.171Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Department of Finance and Tax |
| publisherStr | Department of Finance and Tax |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/43318 An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios Chaibva, Tendayi Chun-Sung, Huang Fama-French Five-Factor Model, Asset Pricing, COVID-19, Industry Portfolios, Model Fit, Factor Loadings, Financial Markets, Regression Analysis 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. 2026-06-12T13:43:30Z 2026-06-12T13:43:30Z 2026 2026-06-12T13:36:22Z Thesis / Dissertation Masters MCom http://hdl.handle.net/11427/43318 en eng application/pdf Department of Finance and Tax Faculty of Commerce University of Cape Town |
| spellingShingle | Fama-French Five-Factor Model, Asset Pricing, COVID-19, Industry Portfolios, Model Fit, Factor Loadings, Financial Markets, Regression Analysis 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_degree_str | Master's |
| title | An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios |
| title_full | An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios |
| title_fullStr | An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios |
| title_full_unstemmed | An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios |
| title_short | An analysis of the Fama and French Five-Factor models significance pre- and post-COVID-19 on 30 U.S. industry portfolios |
| title_sort | analysis of the fama and french five factor models significance pre and post covid 19 on 30 u s industry portfolios |
| topic | Fama-French Five-Factor Model, Asset Pricing, COVID-19, Industry Portfolios, Model Fit, Factor Loadings, Financial Markets, Regression Analysis |
| url | http://hdl.handle.net/11427/43318 |
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