{"title":"Mean-variance portfolio selection in jump-diffusion model under no-shorting constraint: A viscosity solution approach","authors":"Xiaomin Shi, Zuo Quan Xu","doi":"arxiv-2406.03709","DOIUrl":null,"url":null,"abstract":"This paper concerns a continuous time mean-variance (MV) portfolio selection\nproblem in a jump-diffusion financial model with no-shorting trading\nconstraint. The problem is reduced to two subproblems: solving a stochastic\nlinear-quadratic (LQ) control problem under control constraint, and finding a\nmaximal point of a real function. Based on a two-dimensional fully coupled\nordinary differential equation (ODE), we construct an explicit viscosity\nsolution to the Hamilton-Jacobi-Bellman equation of the constrained LQ problem.\nTogether with the Meyer-It\\^o formula and a verification procedure, we obtain\nthe optimal feedback controls of the constrained LQ problem and the original MV\nproblem, which corrects the flawed results in some existing literatures. In\naddition, closed-form efficient portfolio and efficient frontier are derived.\nIn the end, we present several examples where the two-dimensional ODE is\ndecoupled.","PeriodicalId":501045,"journal":{"name":"arXiv - QuantFin - Portfolio Management","volume":"61 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Portfolio Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2406.03709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper concerns a continuous time mean-variance (MV) portfolio selection
problem in a jump-diffusion financial model with no-shorting trading
constraint. The problem is reduced to two subproblems: solving a stochastic
linear-quadratic (LQ) control problem under control constraint, and finding a
maximal point of a real function. Based on a two-dimensional fully coupled
ordinary differential equation (ODE), we construct an explicit viscosity
solution to the Hamilton-Jacobi-Bellman equation of the constrained LQ problem.
Together with the Meyer-It\^o formula and a verification procedure, we obtain
the optimal feedback controls of the constrained LQ problem and the original MV
problem, which corrects the flawed results in some existing literatures. In
addition, closed-form efficient portfolio and efficient frontier are derived.
In the end, we present several examples where the two-dimensional ODE is
decoupled.