Asset Pricing Models Performance in the North America Stock Market

DOI

10.2991/978-94-6463-270-5_22How to use a DOI?

Keywords

Asset Pricing; Five-Factor Model; Stock Returns; COVID-19 Pandemic

Abstract

This study investigates how effectively the five-factor asset pricing model (FF5) elucidates the behavior of stock returns during COVID-19 pandemic and the period of 2000-2023. Using portfolio-level data and regression analysis, this study assesses the model’s ability to capture fluctuations in stock returns. Results in this paper demonstrate that the five-factor model remains robust during the COVID-19 pandemic, with significant relationships between expected returns and factors such as the market risk premium, size, value, profitability, and investment. The model exhibits a high explanatory power, effectively explaining a significant portion of the variability observed in stock returns over longer timeframe. However, it is important to acknowledge the study’s limitations, including its focus on North American portfolios and the relatively short duration of the COVID-19 period analyzed. Future research should explore the model’s performance in other regions and during different market crises. This study adds to the relevant literature by empirically validating the effectiveness of FF5 under both normal and pandemic market conditions, which contributes valuable insights into the model’s applicability and robustness across different market environments. The findings underscore the importance of considering multiple factors in asset pricing models and their adaptability to diverse market environments.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhanqi Kong
PY  - 2023
DA  - 2023/10/29
TI  - Asset Pricing Models Performance in the North America Stock Market
BT  - Proceedings of the 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023)
PB  - Atlantis Press
SP  - 208
EP  - 218
SN  - 2667-1271
UR  - https://doi.org/10.2991/978-94-6463-270-5_22
DO  - 10.2991/978-94-6463-270-5_22
ID  - Kong2023
ER  -