Risk-Return Analysis of Equity Portfolios: Comparison Between CAPM and Fama-French Three Factor Model

Ziyan Tang ()
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Ziyan Tang: Sorbonne Université, La Faculté des Sciences & Ingénierie

A chapter in Proceedings of the 3rd International Conference on Economic Development and Business Culture (ICEDBC 2023), 2024, pp 227-237 from Springer

Abstract: Abstract This article presents an empirical study that examines the explanatory power of these two models in asset portfolio management. The study analyzes the daily returns of 16 prominent companies in 11 industries and the SPDR S&P 500 from January 2012 to December 2021, using ordinary least squares regression to estimate model parameters. The descriptive statistics reveal diverse trends and patterns of returns over the ten-year period. The results suggest that the CAPM model explains only a small portion of the variation in stock returns, with low R-squared values, while the beta coefficients are significant. In contrast, the F-F model provides a improved fit for the data, with higher R-squared values and significant SMB and HML factors for several stocks. The article highlights the importance of carefully considering the choice of model for stock return analysis and discusses the trade-off between model complexity and explanatory power. To ensure the robustness of the findings, the study conducts robustness checks using different time periods and portfolio construction methods. In general, the study adds to the literature by providing empirical evidence on the performance of the CAPM and Fama-French three-factor models in explaining the daily returns of selected stocks. The findings suggest that the Fama-French three-factor model is more suitable for explaining the variation in stock returns than the CAPM model, providing valuable insights for asset portfolio management practitioners.

Keywords: Stock Returns; Portfolio Analysis; Factor Models; Complexity (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-246-0_28

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DOI: 10.2991/978-94-6463-246-0_28

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