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Portfolio Optimization Managing Value at Risk under Heavy Tail Return, using Stochastic Maximum Principle

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Listed:
  • Subhojit Biswas
  • Mrinal K. Ghosh
  • Diganta Mukherjee

Abstract

We consider an investor, whose portfolio consists of a single risky asset and a risk free asset, who wants to maximize his expected utility of the portfolio subject to managing the Value at Risk (VaR) assuming a heavy tailed distribution of the stock prices return. We use a stochastic maximum principle to formulate the dynamic optimisation problem. The equations which we obtain does not have any explicit analytical solution, so we look for accurate approximations to estimate the value function and optimal strategy. As our calibration strategy is non-parametric in nature, no prior knowledge on the form of the distribution function is needed. We also provide detailed empirical illustration using real life data. Our results show close concordance with financial intuition.We expect that our results will add to the arsenal of the high frequency traders.

Suggested Citation

  • Subhojit Biswas & Mrinal K. Ghosh & Diganta Mukherjee, 2019. "Portfolio Optimization Managing Value at Risk under Heavy Tail Return, using Stochastic Maximum Principle," Papers 1908.03905, arXiv.org, revised Nov 2020.
  • Handle: RePEc:arx:papers:1908.03905
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    References listed on IDEAS

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    1. Fotios C. Harmantzis & Linyan Miao & Yifan Chien, 2006. "Empirical study of value-at-risk and expected shortfall models with heavy tails," Journal of Risk Finance, Emerald Group Publishing, vol. 7(2), pages 117-135, March.
    2. Young Kim & Rosella Giacometti & Svetlozar Rachev & Frank Fabozzi & Domenico Mignacca, 2012. "Measuring financial risk and portfolio optimization with a non-Gaussian multivariate model," Annals of Operations Research, Springer, vol. 201(1), pages 325-343, December.
    3. Charles M. Beach & Russell Davidson, 1983. "Distribution-Free Statistical Inference with Lorenz Curves and Income Shares," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(4), pages 723-735.
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