9卷 第6期
Zhejiang University of Finance and Economics, Hangzhou, Zhejiang, 310000, China
纸质出版日期：2025-06-30
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(2025). Research on the Application of Factor Model in Financial Asset Pricing. 发展经济学, 9(6), 18-24.
Chen Anqi.Research on the Application of Factor Model in Financial Asset Pricing[J].Development Economics of China,2025,09(06):18-24.
(2025). Research on the Application of Factor Model in Financial Asset Pricing. 发展经济学, 9(6), 18-24. DOI： 10.47297/wspdecWSP2515-797304.20250906.
Chen Anqi.Research on the Application of Factor Model in Financial Asset Pricing[J].Development Economics of China,2025,09(06):18-24. DOI： 10.47297/wspdecWSP2515-797304.20250906.
As a core tool for financial asset pricing
the evolution and application effectiveness of factor models have always been a focal point in both academic and practical circles. This paper systematically traces the development of factor models from single-factor to multi-factor approaches
delving into the theoretical logic and empirical performance of CAPM
Fama-French's three/five factor models
Carhart's four-factor model
and Q-factor model in financial asset pricing. The study reveals that single-factor models (such as CAPM) provide a foundational framework for asset pricing
but their explanatory power is limited in complex market environments due to constrained market assumptions. Multi-factor models significantly enhance the explanatory capacity for stock cross-sectional returns by incorporating factors like size
value
momentum
and earnings. The Q-factor model further integrates corporate fundamental factors
demonstrating stronger applicability in the Chinese market. Additionally
while the integration of ESG factors with traditional multi-factor models has not yet significantly improved explanatory power
it has become an important direction for future research. In light of increasing market volatility and evolving investment philosophies
this paper proposes that factor models require improvements in nonlinear relationship characterization
behavioral finance factor incorporation
and market anomaly detection
providing theoretical references for building more adaptive asset pricing frameworks.
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