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! ]

Issues of Aggregation Over Time of Conditional Heteroscedastic Volatility Models: What Kind of Diffusion Do We Recover?

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Amine Trifi (University of Paris 1 Sorbonne)
Abstract

Continuous-time models play a central role in the theory of finance whereas empirical finance makes use of discrete-time models. This article investigates the connection between the two classes of models, particularly between conditional heteroscedastic and diffusion processes. As was advocated earlier by Stroock and Varadhan (1979), under some sets of conditions ARCH-type models weakly (in distribution) converge to diffusion processes as the time interval shrinks to zero. We provide the required set of conditions that ensures such a convergence and focus on the kind of the diffusion limit recovered. In the general setting, the diffusion is bivariate and driven by two possibly correlated Brownian motions. We illustrate this result for particular GARCH(1,1) specifications, the augmented GARCH (1,1) and a non-linear specification CEV-ARCH. By imposing an alternate set of conditions regarding the speed of convergence of parameters, a degenerate case is obtained. In the latter, the diffusion limit is governed by a single Brownian motion characterizing the price process while the volatility process becomes deterministic. Finally, we propose a discrete-time heteroscedastic model which shares various properties with ARCH-type models and converges to the complete model with stochastic volatility (CMSV) introduced by Hobson and Rogers (1998) for which the price and the volatility processes are driven by the same Brownian motion. Our analysis bears directly on the market completeness and unicity of asset prices issues.

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://www.bepress.com/cgi/viewcontent.cgi?article=1314&context=snde
File Format: application/pdf
File Function:
Download Restriction: Subscription to the journal may be required to access full texts.

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.

Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 10 (2006)
Issue (Month): 4 ()
Pages: 1314-1314
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:bep:sndecm:10:2006:4:1314-1314

Note: oai:bepress:snde-1314
Contact details of provider:
Web page: http://www.bepress.com/snde/

Order Information:
Web: http://www.bepress.com/subscriptions.html

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: GARH diffusions approximations market completeness CMSV

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. Thierry Jeantheau, 2004. "A link between complete models with stochastic volatility and ARCH models," Finance and Stochastics, Springer, vol. 8(1), pages 111-131, January. [Downloadable!] (restricted)
  2. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38. [Downloadable!] (restricted)
  3. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-27, July. [Downloadable!] (restricted)
    Other versions:
  4. Higgins, Matthew L & Bera, Anil K, 1992. "A Class of Nonlinear ARCH Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-58, February. [Downloadable!] (restricted)
    Other versions:
  5. Peter Ritchken & Rob Trevor, 1999. "Pricing Options under Generalized GARCH and Stochastic Volatility Processes," Journal of Finance, American Finance Association, vol. 54(1), pages 377-402, 02. [Downloadable!] (restricted)
  6. Meddahi, Nour & Renault, Eric, 2004. "Temporal aggregation of volatility models," Journal of Econometrics, Elsevier, vol. 119(2), pages 355-379, April. [Downloadable!] (restricted)
  7. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 6(2), pages 327-43. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? You too can volunteer for RePEc, for example by encouraging others to register as authors.

This page was last updated on 2008-8-3.


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.