A Study on the Influencing Factors of Stock Returns Based on PCA -LASSO Model

Shan-shan ZHANG, Tong-yu LU, Shao-qi QIN, Xue WANG

Abstract


This paper analyzes the influence factors to explain the cross-section of expected returns. Our paper proposes the PCA-LASSO model and its reduced model, comparing them with the results of traditional linear regression model and LASSO regression model. The results show that the proposed PCA-LASSO model and its reduced model are superior to the existing two methods in the prediction of the stock returns of the industry. For practical applications, the research method proposed in this paper has wide applicability and the research conclusion can provide important reference for the securities investors.

Keywords


PCA-LASSO model, Stock returns, Influencing factors, Out of sample prediction


DOI
10.12783/dtcse/cmsam2017/16370

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