This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

The extremal index for GARCH(1,1) processes with t-distributed innovations

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
F. Laurini
J. A. Tawn ()
Abstract

Generalised autoregressive conditional heteroskedastic (GARCH) processes have wide application in financial modelling. To characterise the extreme values of this process the extremal index is required. Mikosch and Starica (2000) derive the extremal index for the squared GARCH(1,1) process. Here we propose an algorithm for the evaluation of the extremal index and for the limiting distribution of the size of clusters of extremes for GARCH(1,1) processes with t-distributed innovations, and tabulate values of these characteristics for a range of parameters of the GARCH(1,1) process. This algorithm also enables properties of other cluster functionals to be evaluated.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://swrwebeco.econ.unipr.it/RePEc/pdf/VII_2006-01.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Department of Economics, Parma University (Italy) in its series Economics Department Working Papers with number 2006-SE01.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length: 23 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:par:dipeco:2006-se01

Contact details of provider:
Postal: Via J.F. Kennedy 6, 43100 PARMA (Italy)
Phone: 0521/902454
Fax: 0521/902400
Email:
Web page: http://economia.unipr.it/de
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Andrea Lasagni).

Related research
Keywords: clusters extreme value theory extremal index finance GARCH multivariate regular variation

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

This paper has been announced in the following NEP Reports:

References listed on IDEAS
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.:
  1. Paola Bortot & Stuart Coles, 2003. "Extremes of Markov chains with tail switching potential," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 65(4), pages 851-867. [Downloadable!] (restricted)
  2. Christopher A. T. Ferro & Johan Segers, 2003. "Inference for clusters of extreme values," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 545-556. [Downloadable!] (restricted)
  3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? You can include your works in the database easily by uploading them on the Munich Personal RePEc Archive (MPRA) if you do not have access to an institutional RePEc archive.

This page was last updated on 2008-11-13.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.