Exploration of Remaining Issues in Capital Asset Pricing Model: Hypothesis Bias and Effectiveness of Variables

The Capital Asset Pricing Model (CAPM) is a cornerstone of modern finance, yet its strict assumptionsparticularly market equilibrium and homogeneous investor expectationslimit real-world accuracy. This study examines two key limitations: (1) how market equilibrium assumptions overlook dynamic price adjustment processes, and (2) why the beta coefficient fails to fully explain asset pricing risks. Using numerical examples and empirical tests, people demonstrate that CAPM's predictions systematically diverge when comparing pre- and post-equilibrium states, while asset scale variations and anomalies like firm size effects further weaken beta's reliability. These results reveal fundamental constraints: equilibrium logic ignores transitional market behaviors, and beta oversimplifies multidimensional risks. Although CAPM remains a vital theoretical tool, its practical application requires acknowledging these limitations. To enhance relevance, future research should develop multi-factor models integrating dynamic equilibrium frameworks, behavioral insights, and technological innovations like machine learning. This evolution could bridge the gap between CAPMs theoretical elegance and the complexity of actual financial markets.