Quantitative Stock Selection Strategy Analysis Based on Multi-factor Model Under the Epidemic Situation

¹ Shenzhen MSU-BIT University, Computational Math and Controls Department, 518172 Shenzhen, China
² Tianjin Renai College, Finance Engineering Department, 301636 Tianjin, China
³ Wenzhou Business College, Computer Science Department, 325035 Wenzhou, China

^* Corresponding author: 1811000232@mail.sit.edu.cn
^† These authors contributed equally.

Abstract

Contemporarily, COVID-19 undoubtedly had a profound impact on the current Chinese economy, as well as presented various challenges and opportunities for different industries in China. As a matter of fact, these changes may profoundly affect the future development trends and competitive landscape of industries. In recent years, the number of stock investors had continued to increase, surpassing 200 million in 2022. In a highly competitive market, the ability to select high-quality stocks often determines the final returns. This study selected the constituent stocks of the “CSI 500” as the “stock pool” for stock selection between 2020 and 2023. By analysing the degree of factor exposure, the correlation between factors, and IC values of factors, suitable and effective factor combinations were selected, and an evaluation model was established using multiple regression analysis to obtain a trading strategy. To ensure its feasibility and rationality, the strategy was simulated using backtesting before actual trading, ultimately aiming to achieve excess alpha returns.