User Classification And Investment Advising Based On Transaction Behavior Of Securities Market Investors

Economic development has not only brought us technological changes,but also has driven people's strong desire for investment On one hand,the rapid development of China's securities market in recent years has made it become the main choice for people to invest;on the other hand,China's securities market is a market with its own characteristics.Many small and medium-sized individual investors and highly dispersed investor structure,have caused a large number of small and medium-sized individual investors to face risks in the market.Investment consultants and securities companies,as professional representatives to guide investors in investment activities,should safeguard the legitimate rights of investors,provide quality and effective services and advice to investors,and help investors to guard against risks.In past,investment consultants were subject to time,space and labor costs,and often only served high-value customers.The development of Internet technology brought about by technological changes made investment advisors available to small and medium-sized individual investors.How to effectively provide consulting services to individual investors is a focus of future"customer-centric" securities companies.This paper has deeply studied the research of domestic and foreign scholars on user classification and investor appropriateness management.Combined with the real data of users obtained from a securities company's Xiamen sales department,this paper constructs a model that can dynamically obtain user preference data and changes,thus making it even more convenient and professional investment consultants combine business experience to provide investors with appropriate services and advice.This paper starts from the user's trading behavior and selects a time period,in this time period,the user's trading behavior characteristics will reflect the user's real trading status.We use these data to construct the user's trading behavior characteristic variables.By give them different directions,we construct the user's product preference model,the user's trading time preference model and the user's comprehensive behavioral preference model.At the same time,this paper constructs a model that can automatically discriminate user's trading style by using the derived data obtained during the construction of the three models and user's own attribute characteristics.The effect of the model is satisfactory.Compared with the past methods of using questionnaires to obtain user information and related services,the results of this paper can overcome the limitations of the questionnaire form in time and space,dynamically obtain the data of user's trading preferences and transaction style changes.Convenient for investment consultants and companies to better track users and provide timely and efficient services,to win the loyalty of users,and at the same time reduce the waste of human and material resources to a certain extent,and create greater value for the enterprise.