Computational Economics

, Volume 29, Issue 3–4, pp 333–354 | Cite as

Portfolio optimization when risk factors are conditionally varying and heavy tailed

Original Paper


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.


Multivariate stable distribution Index model Portfolio optimization Value-at-risk Model adequacy 


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Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  • Toker Doganoglu
    • 1
    • 2
  • Christoph Hartz
    • 3
  • Stefan Mittnik
    • 3
    • 4
    • 5
    • 6
  1. 1.Center for Information and Network EconomicsUniversity of MunichMunichGermany
  2. 2.Faculty of Arts and SciencesSabanci UniversityIstanbulTurkey
  3. 3.Department of StatisticsUniversity of MunichMunichGermany
  4. 4.Ifo Institute for Economic ResearchMunichGermany
  5. 5.Center for Financial StudiesFrankfurtGermany
  6. 6.Institute of StatisticsLudwig-Maximilians-Universität MünchenMünchenGermany

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