Portfolio optimization when risk factors are conditionally varying and heavy tailed

Doğanoğlu, Toker and Hartz, Christoph and Mittnik, Stefan (2007) Portfolio optimization when risk factors are conditionally varying and heavy tailed. Computational Economics, 29 (3-4). pp. 333-354. ISSN 1572-9974

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Official URL: http://springerlink.metapress.com/content/t0354j67u7217361/?p=0fff01bbcbc44f78bb1f0200fe117528&pi=0


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 distribu- tion 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 retain- ing 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.

Item Type:Article
Uncontrolled Keywords:Multivariate stable distribution; index model; portfolio optimization; value-at-risk; model adequacy.
Subjects:H Social Sciences > HG Finance
ID Code:193
Deposited By:Uğur Toker Doğanoğlu
Deposited On:19 Dec 2006 02:00
Last Modified:17 Sep 2019 13:14

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