Dynamic portfolio optimization using mean-semivariance

Multi-period stochastic optimization;Robust optimization;Portfolio optimization;Piecewise quadratic qptimization;Parametric qptimization

Morris, Carl ; Ayhan, Hayriye Deng, Shijie Industrial and Systems Engineering Pokutta, Sebastian White, Chelsea C. Xu, Jun ; Ayhan, Hayriye

University:Georgia Institute of Technology

Department:Industrial and Systems Engineering

关键词: Multi-period stochastic optimization;    Robust optimization;    Portfolio optimization;    Piecewise quadratic qptimization;    Parametric qptimization;   

Others  :  https://smartech.gatech.edu/bitstream/1853/59245/1/MORRIS-DISSERTATION-2017.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

This dissertation studies the mean-semivariance portfolio optimization problem.We describe the relationship of this kind of optimization in the context of other types of portfolio optimization.We construct a novel analysis of mean-semivariance in the context of piecewise quadratic optimization.The unique structure of mean-semivariance is leveraged to provide insight into properties of the optimal portfolio as a function of its key input parameters.This characterization allows us to introduce a new approach to solving a multi-period dynamic mean-semivariance portfolio problem.The proposed methodology provides significant improvements over naive approaches not leveraging the unique structure of the mean-semivariance value function.Finally, we develop a novel, distributionally robust piecewise quadratic formulation using semidefinite programming.We apply the robust formulation to the mean-semivariance portfolio problem to construct a distributionally robust mean-semivariance portfolio.We prove that the robust mean-semivariance portfolio is actually equivalent to the classical mean-variance portfolio.