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Portfolio Optimization Within Mixture Of Distributions

Author

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  • Rania Hentati

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jean-Luc Prigent

    (THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique)

Abstract

The recent financial crisis has highlighted the necessity to introduce mixtures of probability distributions in order to improve the estimation of asset returns and in particular to better take account of risks. Since Pearson (1894), these mixtures have been intensively used in many scientific fields since they provide very convenient mathematical tools to examine various statistical data and to approximate many probability distributions. They are typically introduced to model the choice of probability distributions among a given parametric family. The coefficients of the mixture usually correspond to the relative frequencies of each possible parameter. In this framework, we examine the single-period portfolio choice model, which has been addressed in the partial equilibrium framework, by Brennan and Solanki (1981), Leland (1980) and Prigent (2006). We consider an investor who wants to maximize the expected utility of the value of his portfolio consisting of one risk-free asset and one risky asset. We provide and analyze the solution for log return with mixture distributions, in particular for the mixture Gaussian case. The optimal portfolio is characterized for arbitrary utility functions. Our results show that mixture of distributions can have significant implications on the portfolio management.

Suggested Citation

  • Rania Hentati & Jean-Luc Prigent, 2011. "Portfolio Optimization Within Mixture Of Distributions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00607105, HAL.
    • Handle: RePEc:hal:cesptp:hal-00607105
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    References listed on IDEAS

    as
    1. Brennan, M.J. & Solanki, R., 1981. "Optimal Portfolio Insurance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(3), pages 279-300, September.
    2. Hentati Rania & Prigent Jean-Luc, 2011. "On the maximization of financial performance measures within mixture models," Statistics & Risk Modeling, De Gruyter, vol. 28(1), pages 63-80, March.
    3. Damiano Brigo & Fabio Mercurio, 2002. "Lognormal-Mixture Dynamics And Calibration To Market Volatility Smiles," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 427-446.
    4. Leland, Hayne E, 1980. "Who Should Buy Portfolio Insurance?," Journal of Finance, American Finance Association, vol. 35(2), pages 581-594, May.
    5. K. E. Basford & G. J. McLachlan, 1985. "Likelihood Estimation with Normal Mixture Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(3), pages 282-289, November.
    6. Alexander, Carol, 2004. "Normal mixture diffusion with uncertain volatility: Modelling short- and long-term smile effects," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 2957-2980, December.
    7. P. Carr & D. Madan, 2001. "Optimal positioning in derivative securities," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 19-37.
    8. Mondher Bellalah & Marc Lavielle, 2002. "A Decomposition of Empirical Distributions with Applications to the Valuation of Derivative Assets," Multinational Finance Journal, Multinational Finance Journal, vol. 6(2), pages 99-130, June.
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    Cited by:

    1. Eric Luxenberg & Stephen Boyd, 2022. "Portfolio Construction with Gaussian Mixture Returns and Exponential Utility via Convex Optimization," Papers 2205.04563, arXiv.org, revised Aug 2022.

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