Researcher ORCID Identifier
https://orcid.org/0009-0007-6351-485X
Graduation Year
2025
Date of Submission
11-2024
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
Economics
Second Department
Mathematical Sciences
Reader 1
Benjamin Gillen
Terms of Use & License Information
Rights Information
@ 2025 Kevin M Jiang
Abstract
Frazzini and Pedersen’s (2013) Betting Against Beta is an investment strategy that exploits a well-documented anomaly in the Capital Asset Pricing Model. This anomaly is called the beta anomaly, which states that the model overestimates the risk-adjusted returns of high-beta assets and underestimates the risk-adjusted returns of low-beta assets. According to the beta anomaly, betas and alphas should be negatively correlated. Frazzini and Pedersen prove that an investor is able to generate positive abnormal returns by holding a long position in low-beta assets and a short position in high-beta assets. They also show that their Betting Against Beta factor delivers statistically significant returns when adjusted for multiple factors. My research seeks to test the significance of the beta anomaly in the market factor when adjusted for factors used in the Fama-French 5-Factor and Carhart 4-Factor models that control for the known size, value, momentum, profitability, and investment factors. I find that the beta anomaly loses significance in the market factor when adjusted for the Fama-French 5-Factor model, proving that Frazzini and Pedersen’s results are not robust. I also test for a factor beta anomaly across the size, value, momentum, profitability, and investment factors, as well as the significance of style beta anomalies when adjusted for additional factors. I find that the HML, RMW, and CMA factors show statistically strong patterns that can be made into effective investment strategies.
Recommended Citation
Jiang, Kevin, "Betting Against All Betas: Do Fama-French-Carhart Factors Share the Beta Anomaly?" (2025). CMC Senior Theses. 3845.
https://scholarship.claremont.edu/cmc_theses/3845
Data Repository Link
https://github.com/kjiang25/Betting-Against-All-Betas
Included in
Finance and Financial Management Commons, Management Sciences and Quantitative Methods Commons, Portfolio and Security Analysis Commons