Portfolio optimization when risk factors are conditionally varying and heavy tailed

Toker Doganoglu, Christoph Hartz and Stefan Mittnik

No 2006/24, CFS Working Paper Series from Center for Financial Studies (CFS)

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.

Keywords: Multivariate Stable Distribution; Index Model; Portfolio Optimization; Value-at- Risk; Model Adequacy (search for similar items in EconPapers)
JEL-codes: C13 C32 G11 G14 G18 (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Portfolio optimization when risk factors are conditionally varying and heavy tailed (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:cfswop:200624

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