Dynamic mean–VaR portfolio selection in continuous time

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

12 Scopus Citations
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Author(s)

  • Ke ZHOU
  • Jiangjun GAO
  • Duan LI
  • Xiangyu CUI

Detail(s)

Original languageEnglish
Pages (from-to)1631-1643
Journal / PublicationQuantitative Finance
Volume17
Issue number10
Online published10 Apr 2017
Publication statusPublished - 2017
Externally publishedYes

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.

Research Area(s)

  • Continuous time models, Martingales, Portfolio optimization, Risk management, Value at risk

Citation Format(s)

Dynamic mean–VaR portfolio selection in continuous time. / ZHOU, Ke; GAO, Jiangjun; LI, Duan et al.
In: Quantitative Finance, Vol. 17, No. 10, 2017, p. 1631-1643.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review