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Risk Sensitive Portfolio Optimization in a Jump Diffusion Model with Regimes

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  • Milan Kumar Das
  • Anindya Goswami
  • Nimit Rana

Abstract

This article studies a portfolio optimization problem, where the market consisting of several stocks is modeled by a multi-dimensional jump-diffusion process with age-dependent semi-Markov modulated coefficients. We study risk sensitive portfolio optimization on the finite time horizon. We study the problem by using a probabilistic approach to establish the existence and uniqueness of the classical solution to the corresponding Hamilton-Jacobi-Bellman (HJB) equation. We also implement a numerical scheme to investigate the behavior of solutions for different values of the initial portfolio wealth, the maturity, and the risk of aversion parameter.

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  • Milan Kumar Das & Anindya Goswami & Nimit Rana, 2016. "Risk Sensitive Portfolio Optimization in a Jump Diffusion Model with Regimes," Papers 1603.09149, arXiv.org, revised Jan 2018.
    • Handle: RePEc:arx:papers:1603.09149
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    References listed on IDEAS

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    1. Jan Kallsen, 2000. "Optimal portfolios for exponential Lévy processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 51(3), pages 357-374, August.
    2. Hunt, Julien & Devolder, Pierre, 2011. "Semi-Markov regime switching interest rate models and minimal entropy measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3767-3781.
    3. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
    4. Dieter Sondermann, 2006. "Introduction to Stochastic Calculus for Finance," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-34837-5, October.
    5. Hunt, Julien & Devolder, Pierre, 2011. "Semi Markov regime switching interest rate models and minimal entropy measure," LIDAM Discussion Papers ISBA 2011010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
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    Cited by:

    1. Milan Kumar Das & Anindya Goswami, 2019. "Testing of binary regime switching models using squeeze duration analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-20, March.
    2. Lijun Bo & Huafu Liao & Xiang Yu, 2017. "Risk Sensitive Portfolio Optimization with Default Contagion and Regime-Switching," Papers 1712.05676, arXiv.org, revised Oct 2018.
    3. Milan Kumar Das & Anindya Goswami & Sharan Rajani, 2023. "Inference of Binary Regime Models with Jump Discontinuities," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 49-86, May.
    4. Minglian Lin & Indranil SenGupta, 2021. "Analysis of optimal portfolio on finite and small time horizons for a stochastic volatility market model," Papers 2104.06293, arXiv.org.
    5. Milan Kumar Das & Anindya Goswami & Sharan Rajani, 2019. "Inference of Binary Regime Models with Jump Discontinuities," Papers 1910.10606, arXiv.org, revised Mar 2022.
    6. Marcin Pitera & {L}ukasz Stettner, 2022. "Discrete-time risk sensitive portfolio optimization with proportional transaction costs," Papers 2201.02828, arXiv.org.
    7. Milan Kumar Das & Anindya Goswami, 2018. "Testing of Binary Regime Switching Models using Squeeze Duration Analysis," Papers 1807.04393, arXiv.org, revised Aug 2018.
    8. Laura Eslava & Fernando Baltazar-Larios & Bor Reynoso, 2022. "Maximum Likelihood Estimation for a Markov-Modulated Jump-Diffusion Model," Papers 2211.17220, arXiv.org.

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