Research Article
Application of Multi-Factor Quantitative Stock Selection Strategy Based on Scoring Method: Evidence from the CSI 300 Component Stocks
@INPROCEEDINGS{10.4108/eai.28-10-2022.2328426, author={Zikun Chen and Min Hong and Ruya Lin}, title={Application of Multi-Factor Quantitative Stock Selection Strategy Based on Scoring Method: Evidence from the CSI 300 Component Stocks}, proceedings={Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China}, publisher={EAI}, proceedings_a={FFIT}, year={2023}, month={4}, keywords={quantitative investment; quantitative stock selection; scoring method; multi-factor model}, doi={10.4108/eai.28-10-2022.2328426} }- Zikun Chen
Min Hong
Ruya Lin
Year: 2023
Application of Multi-Factor Quantitative Stock Selection Strategy Based on Scoring Method: Evidence from the CSI 300 Component Stocks
FFIT
EAI
DOI: 10.4108/eai.28-10-2022.2328426
Abstract
With the wide application of computers and the continuous improvement of big data processing methods, the methods and theories of quantitative investment can better and faster adapt to the rapid development of the current financial market, and this method is gradually becoming one of the main means of financial investment analysis. This article selects CSI 300 constituent stocks as sample stocks, intercepts financial and market data from 2012 to 2021, establishes an effective factor database, and tests the effectiveness of each factor. Finally, a more robust factor affecting stock returns is obtained. This paper evaluates the performance of the quarterly returns and cumulative returns obtained by grouping stocks by the selected factors and obtains the validity of the established model.