Portfolio Optimization Theory Of Insurance Funds With Second-order Stochastic Dominance Constraints

Insurance companies proft from the underwriting and investment.And theexternal environment have a major infuence on the underwriting proft,such aspolicy changes and market conditions.However investment income depends onthe insurance companies’ ability on investment.Therefor,the insurance companieshave to choose reasonable assets portfolio and proportion of investment,which canmake the insurance companies obtain high returns on investment.Currently,there are many methods to construct the assets portfolio,whichcan get diferent proportions of investment.At he moment stochastic dominancehas been widely applied to the economic and fnancial feld.In this paper,we ap-plied the portfolio optimization model with second-order stochastic dominanceof insurance funds.When we solve the portfolio optimization model of insurancefunds with second-order stochastic dominance constraints,the non-smooth oper-ator makes it difcult solve.On the other hand,the insurance companies predictthe future investment that is based on the historical data.So when the rate ofreturns and the benchmark yield are all discrete and limited distributions.we usethe smoothing function to approximate the non-smooth function,which simplifesthe solution of the model.This essay contains fve chapters,The frst chapter introduces the study back-ground and efects of investment portfolio and the application of insurance fund-s.At the same time,it introduces the main work of all and explains the symbol-s and the basic concept of the portfolio optimization model of insurance fundswith second-order stochastic dominance constraints.The second chapter buildsthe portfolio optimization model of insurance funds with second-order stochas-tic dominance constraints,which is based on the portfolio optimization model ofinsurance funds with general mean-variance.The third chapter discusses its opti-mization theory.The fourth chapter analysis a smoothing approach,when the rateof returns and the benchmark yield are all discrete and limited distributions.Theffth chapter is the conclusions of this paper and future research prospects.