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Application of Fama-Fench three-factor model in Chinese A-share market --Based on SVM machine learning model

Pengyun Wang, Guanying Dai, Weixin Zhang

Abstract


How to apply machine learning in the field of financial investment has been a hot research topic in academia and finance. In this paper, the support vector machine method (SVM) in machine learning is combined with Fama-Fench three-factor model to construct a new quantitative investment strategy, and the empirical analysis is carried out by using A-shares. Research shows that support vector machine (SVM) combined with the traditional three-factor model can build a more effective portfolio.


Keywords


Machine Learning; Fama-Fench three-factor model; SVM

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References


Fama ,E.F.& K.R .French(1992), “The cross-section of expected stock returns”, Journal of Finance 47:427-466.

Fama , E.F.& K.R .French (1993), “Common risk factors in the returns on stocks and bonds”,Journal of Financial Economics 3:33-56.

Cortes C, Vapnik V. Support-Vector Networks.[J].Machine Learning,1995,20(3):2 73-297.




DOI: https://doi.org/10.18282/ff.v10i2.1944

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