方法对比
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| 多因子风险模型（Fama-French, APT）× | 普通最小二乘法 (OLS) 回归× | |
|---|---|---|
| 领域≠ | 金融学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1993 | 2019 |
| 提出者≠ | Fama & French (factor model); Ross (Arbitrage Pricing Theory) | Wooldridge (textbook treatment); classical least squares |
| 类型≠ | Multi-factor linear regression model | Linear regression |
| 开创性文献≠ | Fama, E. F., & French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 33(1), 3-56. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| 别名≠ | Fama-French model, Fama-French three-factor model, Fama-French five-factor model, arbitrage pricing theory | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| 相关 | 5 | 5 |
| 摘要≠ | A factor risk model is a multi-factor framework that links asset returns to systematic risk factors such as the market, value, size, and momentum. The Fama-French three- and five-factor models (1993) and Ross's Arbitrage Pricing Theory (1976) decompose portfolio risk and detect alpha. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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