Analysis of stock selection strategy of multi-factorial model based on rotation factor and investor sentiment

Financial engineering, Guangdong University of Finance & Economics, 510220 Guangzhou, China

^* Corresponding author: chenyiman@student.gdufe.edu

Abstract

With the wide application of advanced technologies including AI which with high precision and automation level, financial technology has shown a progressive trend, and quantitative trading strategies have bright prospect. Based on China’s A-share market, this study constructs a quantitative strategy for stock selection by combining the industry rotation effect with a multi-factor model considering investor sentiment. Firstly, the strategy screens the target industries according to the rotation factor calculated by PER, and then determine the stocks by the multi-factor model formed by the factors after effective test. In this study, the effectiveness of the strategy is verified through six constructed back-test portfolios from both sides. According to the analysis, the return of the strategy considering the rotation effect and investor sentiment is higher than the market. The comparison of the impact of the rotation factor and the emotional factor shows that the change of macro and middle environment has a greater impact on stock prices than the micro level. Up to now, there are few stock selection strategies considering both rotation effect and investor sentiment. These results attempt to supplement this aspect and enrich the field of asset pricing.