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Multivariate extremes, aggregation and risk estimation

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Author Info
Michel Dacorogna (Zürich Re)
Höskuldur Ari Hauksson
Thomas Domenig
Ulrich Müller
Gennady Samorodnitsky

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Abstract

We briefly introduce some basic facts about multivariate extreme value theory and present some new results regarding finite aggregates and multivariate extreme value distributions. Based on our results high frequency data can considerably improve quality of estimates of extreme movements in financial markets. Secondly we present an empirical exploration of what the tails really look like for four foreign exchange rates sampled at varying frequencies. Both temporal and spatial dependence is considered. In particular we estimate the spectral measure, which along with the tail index, completely determines the extreme value distribution. Lastly we apply our results to the problem of portfolio optimisation or risk minimization. We analyze how the expected shortfall and VaR scale with time horizon and find that this scaling is not by a factor of square root of time as is frequently used, but by a different power of time. We show that the accuracy of risk estimation can be drastically improved by using hourly or bihourly data.

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Publisher Info
Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Workshop Papers, January 2001 with number P2.

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Date of creation: 04 Jan 2001
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Handle: RePEc:ams:cdws01:p2

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Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands
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Fax: + 31 20 525 52 83
Web page: http://www.fee.uva.nl/cendef/
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  1. Ardia, David, 2003. "Analysis of dependencies in low frequency financial data sets," MPRA Paper 12682, University Library of Munich, Germany. [Downloadable!]
  2. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Quantitative Finance Papers cond-mat/0203166, arXiv.org. [Downloadable!]
  3. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research Department. [Downloadable!]
  4. Faruk Selcuk & Ramazan Gencay, 2001. "Overnight Borrowing, Interest Rates and Extreme Value Theory," Departmental Working Papers 0103, Bilkent University, Department of Economics. [Downloadable!]
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  5. Peter Blum & Michel Dacorogna & Lars Jaeger, 2003. "Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations," Risk and Insurance 0311001, EconWPA. [Downloadable!]
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This page was last updated on 2009-11-25.


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