Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model
Tim Bollerslev
The Review of Economics and Statistics, 1990, vol. 72, issue 3, 498-505
Abstract:
A multivariate time series model with time varying conditional variances and covariances, but constant conditional correlations is proposed. In a multivariate regression framework, the model is readily interpreted as an extension of the Seemingly Unrelated Regression (SUR) model allowing for heteroskedasticity. Parameterizing each of the conditional variances as a univariate Generalized Autoregressive Conditional Heteroskedastic (GARCH) process, the descriptive validity of the model is illustrated for a set of five nominal European U.S. dollar exchange rates following the inception of the European Monetary System (EMS). When compared to the pre- EMS free float period, the comovements between the currenciess are found to be significantly higher over the later period. Copyright 1990 by MIT Press.
Date: 1990
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1863)
Downloads: (external link)
http://links.jstor.org/sici?sici=0034-6535%2819900 ... O%3B2-N&origin=repec full text (application/pdf)
Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
Related works:
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:tpr:restat:v:72:y:1990:i:3:p:498-505
Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535
Access Statistics for this article
The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu
More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by The MIT Press ().