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《Journal of Southwest University(Natural Science Edition)》 2019-01
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Multi-Factor Strategy Based on Quantile Regression

ZHOU Liang;Editorial Department,Hunan University of Finance and Economics;  
This paper selects all the annual data of six factors including the size,stock price,price-earnings ratio,momentum,turnover rate and volatility of the CSI 500 Index from the beginning of 2007 to the end of2017,and explores the application of quantile regression in multi-factor stock selection strategy.The results show that:for the single factor,both the size factor and the stock price factor show stronger effects in the high-yield stocks;and the market-to-net ratio,momentum and turnover factor all show stronger effect in the low-yield stocks;the volatility factor in the high yield and low yield stocks have shown strong effects;multifactor stock selection models have shown better than the OLS regression model of investment results,scalestock price model can obtain 43.17% of the annualized yield in the sample interval,while the PBR-Momentum-turnover ratio factor stock selection model can get an annualized yield of 18.48%.
【Fund】: 国家社会科学基金项目(14BJL086);; 湖南省教育厅科学研究项目(14B031)
【CateGory Index】: F832.51
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