• DocumentCode
    1775208
  • Title

    Continuous-time mean-variance portfolio optimization with Safety-First Principle

  • Author

    Yan Xiong ; Jianjun Gao

  • Author_Institution
    Dept. of Autom., Shanghai Jiaotong Univ., Shanghai, China
  • fYear
    2014
  • fDate
    18-20 June 2014
  • Firstpage
    66
  • Lastpage
    71
  • Abstract
    This paper studies the portfolio optimization problem with multiple risk measures. More specifically, we use the variance and the Safety First Principle(SFP) as a combined risk measure in mean-risk portfolio optimization model. As the SFP measures the probability that random variable falls below certain level, combining SFP in the mean-variance formulation helps to control the downside risk of the portfolio return. Due to the complexity of such problem, it is difficult to solve such a problem by the traditional stochastic control approach directly. Under some assumptions of the market structure, we transform the incomplete market to complete one and derive the analytical portfolio policy by using the martingale approach. The simulation results exhibit prominent feature of our model in controlling the downside risk of the portfolio model.
  • Keywords
    continuous time systems; investment; optimisation; probability; random processes; risk management; stochastic processes; SFP; analytical portfolio policy; continuous-time mean-variance portfolio optimization; market structure; martingale approach; mean-risk portfolio optimization model; mean-variance formulation; multiple risk measure; portfolio model; portfolio optimization problem; portfolio return; probability; random variable; safety-first principle; stochastic control approach; Equations; Investment; Optimization; Portfolios; Random variables; Stochastic processes; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control & Automation (ICCA), 11th IEEE International Conference on
  • Conference_Location
    Taichung
  • Type

    conf

  • DOI
    10.1109/ICCA.2014.6870897
  • Filename
    6870897