Estimating VAR-MGARCH models in multiple steps

M. Angeles Carnero and Eratalay M. Hakan
Additional contact information
Eratalay M. Hakan: Dep. Economics, European University at St Petersburg, Russian Federation

Studies in Nonlinear Dynamics & Econometrics, 2014, vol. 18, issue 3, 339-365

Abstract: This paper analyzes the performance of multiple steps estimators of vector autoregressive multivariate conditional correlation GARCH models by means of Monte Carlo experiments. We show that if innovations are Gaussian, estimating the parameters in multiple steps is a reasonable alternative to the maximization of the full likelihood function. Our results also suggest that for the sample sizes usually encountered in financial econometrics, the differences between the volatility and correlation estimates obtained with the more efficient estimator and the multiple steps estimators are negligible. However, when innovations are distributed as a Student-t, using multiple steps estimators might not be a good idea.

Keywords: financial markets; volatility spillovers (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
https://doi.org/10.1515/snde-2012-0065 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
Working Paper: Estimating VAR-MGARCH models in multiple steps (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:18:y:2014:i:3:p:27:n:5

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html

DOI: 10.1515/snde-2012-0065

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().