Research On The Choice Of Basic Asset And Price Competition In Robo-advisor Service

The "New Generation Artificial Intelligence Development Plan"promulgated by the State Council in 2017 has defined the strategic goal of future development for the development of artificial intelligence in China.With the development of science and technology,artificial intelligence will open a new chapter in the financial field.The robo-advisor service as the frontier application of artificial intelligence in the financial field.brought substantial changes to the robo-advisor service of the wealth management industry.and presented a trend of rapid development.China's robo-advisor service began in 2015.The robo-advisor service understands user's needs through questionnaires,uses machine learning methods to optimize data,and builds basic asset pools through model selection.Based on the portfolio theory,it can automatically tailor asset allocation solutions for users with different risk preferences.The robo-advisor can increase user satisfaction by making high-precision judgments on the market.thus achieving its intelligent transformation.By consulting relevant literature.we find that the research of current robo-advisor mainly focuses on business introduction and regulatory policy research.This dissertation attempts to broaden the research perspective of this field and follow the research framework of "status-mechanism-prediction" to study the tendency of asset selection and price competition mechanism of robo-advisor.Firstly,through qualitative analysis,the case study of the operation mechanism of intelligent investment is conducted.and the factors affecting the selection of the basic asset pool of robo-advisor are preliminarily judged.Secondly',we use empirical research to explore the mechanism of robo-advisor,reveal the influencing factors of selection tendency of robo-advisor's asset pool,and analyze the relationship between various factors.Finally,we use theoretical research and data simulation methods to conduct an in-depth analysis of one of the influencing factors(management rates)of robo-advisor.Through the study of the price competition mechanism in the robo-advisor market,we try to predict the price competition mechanism in the robo-advisor market.This dissertation hopes to explore and play a role in the follow-up study.The main work and innovations are as follows:Firstly,we broaden the research perspective of of problems and conform to the development trend of financial technology.The robo-advisor is still an emerging business in China.Through researching on the existing literature,we find that the asset selection and price competition mechanism have rarely been studied by the predecessors.This dissertation attempts to expand the research ideas of robo-advisor,and conducts research on asset selection of robo-advisor and price competition mechanism as research objects.This work combines social attention hotspots,accords with national policy orientation and enriches research results in related fields.which has certain practical significance.Secondly,we use case study methods to explore the operation mechanism of intelligent investment advisory.Due to the novelty of the robo-advisor service,the existing models cannot be simply used in the research.This dissertation conducts a qualitative research on the problem of the robo-advisor service operation mechanism and analyzes the differences between different types of intelligent investment advisory in China and the influencing factors of the choice of basic assets.Construct a three-dimensional influencing factor model of the robo-advisor service on the choice of basic assets.and reveal the direct role of the influencing factors and the regulating role path.Thirdly,empirical analysis is used to explore the practical practices of emerging businesses and provide theoretical support for it.In practice,the asset selection of smart investment service will have certain characteristics,but we do not find relevant research from the literature.This dissertation obtains real data from the capital market,based on the characteristics of China's robo-advisor,uses empirical analysis to study the propensity of robo-advisor's asset selection,tries to provide data explanation for practical operation,and reflects the theory's guidance value to practice.Fourthly,in accordance with the actual operation mode of the new business,a new model is built to analyze the price competition mechanism of the robo-advisor.In the traditional price competition research,the predecessors considered price as the only factor affecting product demand.We find that in the smart investment service network,the demand is not only affected by price.This dissertation introduces the congestion effect in the service network demand model and constructs the demand model considering the crowding effect.Through theoretical analysis and mathematical proof,it can be concluded that there is only one pure strategy Nash equilibrium solution in the price competition of fund management fees in robo-advisor.Applying these theories to practice can provide substantial advice and assistance to the pricing of fund management companies and smart investment companies,as well as the future policy development of regulators.As an exploratory study,this dissertation attempts to expand the research field of robo-advisor.Through the organic combination of theory and work practice,the problems in the current capital market are studied.It provides a heuristic approach for fund management companies,smart investment companies and regulatory authorities,which is of certain practical significance and theoretical value.