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Portfolio optimization when risk factors are conditionally varying and heavy tailed

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Abstract

Assumptions about the dynamic and distributional behavior of risk factors are crucial for the construction of optimal portfolios and for risk assessment. Although asset returns are generally characterized by conditionally varying volatilities and fat tails, the normal distribution with constant variance continues to be the standard framework in portfolio management. Here we propose a practical approach to portfolio selection. It takes both the conditionally varying volatility and the fat-tailedness of risk factors explicitly into account, while retaining analytical tractability and ease of implementation. An application to a portfolio of nine German DAX stocks illustrates that the model is strongly favored by the data and that it is practically implementable.

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Author information

Authors and Affiliations

  1. Center for Information and Network Economics, University of Munich, Munich, Germany

    Toker Doganoglu

  2. Faculty of Arts and Sciences, Sabanci University, Istanbul, Turkey

    Toker Doganoglu

  3. Department of Statistics, University of Munich, Munich, Germany

    Christoph Hartz & Stefan Mittnik

  4. Ifo Institute for Economic Research, Munich, Germany

    Stefan Mittnik

  5. Center for Financial Studies, Frankfurt, Germany

    Stefan Mittnik

  6. Institute of Statistics, Ludwig-Maximilians-Universität München, Akademiestr. I/1, D-80799, München, Germany

    Stefan Mittnik

Authors
  1. Toker Doganoglu
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  2. Christoph Hartz
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  3. Stefan Mittnik
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Correspondence to Stefan Mittnik.

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Doganoglu, T., Hartz, C. & Mittnik, S. Portfolio optimization when risk factors are conditionally varying and heavy tailed. Comput Econ 29, 333–354 (2007). https://doi.org/10.1007/s10614-006-9071-1

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  • DOI: https://doi.org/10.1007/s10614-006-9071-1

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