| The development of quantitative investment in China is becoming more and more mature.Compared with traditional research,it has the natural advantages of processing massive data,wide scope and quick response.At the same time,the rhythm of the market style rotation has accelerated,and the differentiation of the track has increased.In 2021,carbon neutrality becomes the main line of investment,and the prosperity of the new energy vehicle industry will continue.Therefore,optimizing the return characteristics of investment portfolios at the meso-sector level has practical significance.In this context,this paper selects the new energy vehicle industry chain to build stock pool and establishes a multi-factor quantitative model.In order to enhance the interpretability of the model,a prosperity factor is constructed based on the framework of industry prosperity theory,and a multi-factor pricing model that introduces prosperity factors is designed on this basis.The first two chapters of this paper clarify the thesis concept and lay the theoretical foundation.The analysis finds that the selection of factors is generally based on economic logic,and at the same time,new factors are constructed and their validity is verified.Considering that my country has a relatively complete and leading new energy vehicle industry chain,and the new energy vehicle industry is gradually shifting from policy-driven to demand-driven,it is decided that the vertical layout along the industrial chain will be based on the mesoscopic level,from the two dimensions of volume and price.In the downstream,qualitative and quantitative analysis of fundamentals was carried out,and 20 alternative prosperity indicators were obtained.Then,combined with data availability and time difference correlation analysis,11 indicators were selected,and all of them were consistent or leading indicators,which have significance for monitoring changes in industrial prosperity.Afterwards,the principal component analysis method was used to synthesize the statistical factor,the prosperity factor,as one of the explanatory variables of the change in yield.The correlation between the prosperity factor and the operating income of the sector reached 0.766,and the HP filter analysis was further carried out.Afterwards,the prosperity factor should be tested,and a multi-factor index system is constructed.The training period is from October 2017 to April 2021,and the backtest period is from May 2021 to December 2022.The target selection range is the CSI New Energy Vehicle Index constituent stocks and 72 nonconstituent stocks.In terms of factor selection,fundamentally,15 factors are selected to reflect the company’s scale,growth,financial quality and valuation,and 3 factors are selected technically.Combined with the prosperity factor,a total of 19 factors are selected.Through the cross-sectional regression T test,A total of 8 effective factors were screened out by IC test and stratified method test,and redundant factors were eliminated.The prosperity factor has a high correlation with the expected rate of return and is not strongly correlated with other factors.The final effective factors are the priceto-book ratio,net profit growth rate,return on equity,gross profit margin and prosperity.In the stock selection method,the scoring method is studied to build a monthly stock selection model,and the factor weights are obtained by IR weighting.Compared with the 399976.SZ,the annualized excess return of the monthly strategy is 457.59%,and the maximum drawdown is only 14.2%.Therefore,the ability to adjust positions and select stocks is excellent,the investment portfolio has outstanding returns,and the risk control ability is strong.Specifically,the top ten stock positions are gradually tilted from motor electronic control,electronic components and complete vehicles to lithium and cobalt resources and key raw materials,showing the trend from downstream to upstream.Under the context of transmission of demand,there is a change in yield in the chain. |
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