A Comparative Study Of Traditional Quantization Investment And AI Quantization Investment

Quantitative investment,as a trading method to obtain stable returns through quantity statistics,model construction and automatic trading,has become mature in foreign countries,but has not entered a mature stage in China due to institutional factors and restrictions of derivative instruments.At the same time,the great popularity of machine learning also has a great impact on quantitative investment.AI quantization comes into being and has aroused controversy and discussion.Therefore,this paper compared and studied the basic characteristics of traditional quantitative investment and AI quantitative investment,aiming to provide guidance for quantitative investment decisions.The key to quantitative investment is to grasp the market fundamental attributes,stock trend characteristics and other special factors.Therefore,this paper introduces the traditional quantitative basic strategies and evaluation indicators;Then,the AI algorithm is applied to the strategy model of quantitative investment,factor analysis is carried out and taken as the machine learning feature set,and the historical data is trained by learning models such as Xgboost,StockRanker and random forest,etc.,through which the multi-factor stock selection model is obtained.Finally,the traditional quantitative investment and AI quantitative investment are compared and studied through the market value strategy.Finally,we 've come to a conclusion that traditional quantization and AI quantization are desirable strategic models.Moreover,both of them have their own characteristics of investment.Understanding these characteristics can help us avoid risks in the investment process and reduce unnecessary losses.