Analyse the Limitations of the Capital Asset Pricing Model (CAPM) in Risk Measurement Using the Monte Carlo Simulation Method

Ziran Chang ()
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Ziran Chang: Southwestern University Of Finance And Economics

A chapter in Proceedings of the 2025 5th International Conference on Enterprise Management and Economic Development (ICEMED 2025), 2025, pp 717-728 from Springer

Abstract: Abstract This paper critically examines the limitations of the Capital Asset Pricing Model (CAPM) in financial risk measurement by applying the Monte Carlo simulation method. While CAPM remains a foundational model in asset pricing and investment decision-making due to its theoretical simplicity and operability, its reliance on idealised assumptions—such as rational investors, frictionless markets, and normally distributed returns—often diverges from the complexities of real-world financial markets. Using historical data from the Shanghai Stock Exchange and simulating asset return paths through geometric Brownian motion, this study conducts 10,000 iterations to estimate risk indicators, including expected return, standard deviation, and Value at Risk (VaR). The findings reveal that CAPM underestimates risk by oversimplifying market dynamics and relying solely on the beta coefficient, which may fluctuate in volatile markets. In contrast, Monte Carlo simulation captures a broader distribution of outcomes, accounting for market uncertainties and extreme events more effectively. This study not only underscores the inadequacies of CAPM in dynamic environments but also highlights the importance of incorporating simulation-based techniques for more robust risk evaluation. The results offer theoretical insights and practical guidance for investors and financial institutions aiming to enhance the precision and adaptability of their risk assessment frameworks.

Keywords: CAPM; Monte Carlo Simulation; Limitation analysis; Beta (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-811-0_75

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DOI: 10.2991/978-94-6463-811-0_75

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