Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations
AbstractHedge funds are said to be rewarding investments because they have favourable risk-return characteristics on a standalone basis, and because they offer valuable diversification with respect to traditional stock and bond markets. On the other hand, hedge fund returns have a number of characteristics that make their quantitative analysis difficult: distributions are often asymmetric and have an increased tendency towards extreme outcomes ("heavy tails"), and dependence structures with respect to traditional markets are often complex. Moreover, quality and quantity of available data may be limited. In this study, we survey and present a number of quantitative analysis techniques that are able to cope with the particular characteristics of hedge funds, including methods for extreme value analysis and non- standard dependence models.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by EconWPA in its series Risk and Insurance with number 0311001.
Length: 20 pages
Date of creation: 05 Nov 2003
Date of revision:
Note: Type of Document - Acrobat PDF; prepared on Win2000; to print on HP A4; pages: 20
Contact details of provider:
Web page: http://22.214.171.124
hedge funds; risk measurement; risk management;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-11-09 (All new papers)
- NEP-FIN-2003-11-09 (Finance)
- NEP-RMG-2003-11-09 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Michel M. Dacorogna, & Ulrich A. Muller & Olivier V. Pictet & Casper De Vries,, . "The Distribution of Extremal Foreign Exchange Rate Returns in Extremely Large Data Sets," Working Papers 1992-10-22, Olsen and Associates.
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- H. A. Hauksson & M. Dacorogna & T. Domenig & U. Mller & G. Samorodnitsky, 2001.
"Multivariate extremes, aggregation and risk estimation,"
Taylor & Francis Journals, vol. 1(1), pages 79-95.
- Michel Dacorogna & Höskuldur Ari Hauksson & Thomas Domenig & Ulrich Müller & Gennady Samorodnitsky, 2001. "Multivariate extremes, aggregation and risk estimation," CeNDEF Workshop Papers, January 2001 P2, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Peter Blum & Michel Dacorogna, 2003. "Dynamic Financial Analysis - Understanding Risk and Value Creation in Insurance," Risk and Insurance 0306002, EconWPA.
- Ardia, David, 2003. "Analysis of dependencies in low frequency financial data sets," MPRA Paper 12682, University Library of Munich, Germany.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.