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Dynamic mean–VaR portfolio selection in continuous time

Author

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  • Ke Zhou
  • Jiangjun Gao
  • Duan Li
  • Xiangyu Cui

Abstract

The value-at-risk (VaR) is one of the most well-known downside risk measures due to its intuitive meaning and wide spectra of applications in practice. In this paper, we investigate the dynamic mean–VaR portfolio selection formulation in continuous time, while the majority of the current literature on mean–VaR portfolio selection mainly focuses on its static versions. Our contributions are twofold, in both building up a tractable formulation and deriving the corresponding optimal portfolio policy. By imposing a limit funding level on the terminal wealth, we conquer the ill-posedness exhibited in the original dynamic mean–VaR portfolio formulation. To overcome the difficulties arising from the VaR constraint and no bankruptcy constraint, we have combined the martingale approach with the quantile optimization technique in our solution framework to derive the optimal portfolio policy. In particular, we have characterized the condition for the existence of the Lagrange multiplier. When the opportunity set of the market setting is deterministic, the portfolio policy becomes analytical. Furthermore, the limit funding level not only enables us to solve the dynamic mean–VaR portfolio selection problem, but also offers a flexibility to tame the aggressiveness of the portfolio policy.

Suggested Citation

  • Ke Zhou & Jiangjun Gao & Duan Li & Xiangyu Cui, 2017. "Dynamic mean–VaR portfolio selection in continuous time," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1631-1643, October.
  • Handle: RePEc:taf:quantf:v:17:y:2017:i:10:p:1631-1643
    DOI: 10.1080/14697688.2017.1298831
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    References listed on IDEAS

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    Cited by:

    1. Weiping Wu & Yu Lin & Jianjun Gao & Ke Zhou, 2023. "Mean-variance hybrid portfolio optimization with quantile-based risk measure," Papers 2303.15830, arXiv.org, revised Apr 2023.
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    3. Zhu, Pengfei & Tang, Yong & Wei, Yu & Dai, Yimin, 2019. "Portfolio strategy of International crude oil markets: A study based on multiwavelet denoising-integration MF-DCCA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    4. Zongxia Liang & Fengyi Yuan, 2021. "Equilibrium master equations for time-inconsistent problems with distribution dependent rewards," Papers 2112.14462, arXiv.org, revised Apr 2022.

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