Information Advantage And Optimal Portfolio Choice

With the help of the stochastic analysis theory developed by Ito,mathematical fi-nance steps into a new time.A great deal of stochastic models used to characterize thefinancial market have been developed,and the corresponding derivative pricing problemsand portfolio choice problems based on these models are all solved.Being diferent fromthe direction which focuses on the market frame characterization,behavioral financial the-ory focuses on the diference between market participants,it attention that informationasymmetric has great efects on investors’s decisions.But,it is so difcult to characterizeinformation by mathematical models that correlated researches are limited in descriptiveanalysis.This paper has a try to characterize a special class of information diference,and solves the given information portfolio choice problem for investors having diferentinformation under an market model with regime–switching. To make the readers knowour idea quickly, this paper explain how information will afect people’s decisions by agame. In the game, diferent players have diferent optimal strategies to achieve a samegoal, because of diferent information they have. After that, we pay our attention to ourresearch object, the capital market. We build a market model with one riskless asset, onestock from cyclical industry and one stock from noncyclical industry. Then, we definesome representative investors in this market. These representative investors have diferentability in acquiring and dealing with information that has great things to do with the mar-ket. We solve the Mean–Variance portfolio optimization problem for the representativeinvestors given their information and uncover the important relationship between con-ditional Mean–Variance optimization and unconditional Mean–Variance optimization.We solve the Mean–Variance portfolio optimization problem for the representative in-vestors given their information and uncover the important relationship between condi-tional Mean–Variance optimization and unconditional Mean–Variance optimization.