MCMC Estimation of the COGARCH(1,1) Model
This paper presents a Markov chain Monte Carlo (MCMC)-based estimation procedure for the COGARCH(1,1) model driven by a compound Poisson process. The COGARCH model is a continuous-time analogue to the discrete-time GARCH model and captures many of the stylized facts of financial time series, as has been shown in various papers. Principles for the estimation of point processes by MCMC are adapted to the special structure of the COGARCH(1,1) model. The algorithm uses discrete GARCH-type equations on a random grid which changes in each iteration of the MCMC sampler. Moreover, exact solutions of the volatility SDE of the COGARCH(1,1) model are available on this grid, so that no approximations of the COGARCH equations are necessary. The method is also applicable to irregularly spaced observations. A simulation study illustrates the quality of the MCMC estimates. Finally we fit the COGARCH(1,1) model to high-frequency data of the S&P500. Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org, Oxford University Press.
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 8 (2010)
Issue (Month): 4 (Fall)
|Contact details of provider:|| Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK|
Fax: 01865 267 985
Web page: https://academic.oup.com/jfec
More information through EDIRC
|Order Information:||Web: http://www.oup.co.uk/journals|
When requesting a correction, please mention this item's handle: RePEc:oup:jfinec:v:8:y:2010:i:4:p:481-510. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.