Optimization Design Of Multi-factor Alpha Quantitative Stock Selection Strategy Of RG Company

Quantitative investment plays an important role in today's financial industry,and it is also the future development direction of finance.The multi factor stock selection model is also one of the most widely used and practical models in the quantitative model.This paper starts from the existing Alpha multi factor quantitative stock selection model of the company that I practice,seeks for the optimal design of the existing model of the company,and solves the practical application problems.According to the effective market theory,optimize the existing model of the company by seeking the optimization way of new factors and realizing the diversity of factors so as to achieve the purpose of improving excess return and reducing portfolio risk.Firstly,this paper introduces the background of quantitative investment,the development and application of multi factor quantitative stock selection model,and finds out the shortcomings of the existing model of the company,such as old factors and insufficient types of factors.Then,by studying other mature quantitative investment fund models in the existing market,we can find a reasonable optimization way,and introduce the development and application of multi factor quantitative stock selection model The basic situation and investment strategy of some mature multi factor quantitative funds in the current market.The empirical part of optimization mainly introduces the guiding ideology and selection criteria of factor optimization,and selects the chip distribution factors and volatility factors that are not included in the company factor system at this stage.The chip distribution factors are profit share,activity chip,low chip density index,current price relative position,and dispersion process measurement.The volatility factors mainly include path volatility factor and signal-to-noise factor.Finally,through the validity analysis and verification analysis of single factor,the measure factors of decentralization process and the relative position factors of current price are selected from the chip factors.Among the volatility factors,path volatility index factor,signal-to-noise ratio increment factor and time price consistency index factor are selected.Finally,after adding new factors into the model,compared with the results of the original model,the interval rate of return increases,the maximum reversion value decreases,and the sharp ratio of the model also increases significantly.A series of data shows that updating the factor base can improve the model rate of return,and also improve the low sharp ratio of the model.The sharp ratio is obtained by measuring the fund unit risk.The improvement of this part shows that the excess return of fund unit risk has been improved after the optimization of the model.