An empirical comparison of alternative models in estimating Value-at-Risk: evidence and application from the LSE
by Everton Dockery, Miltos Efentakis
International Journal of Monetary Economics and Finance (IJMEF), Vol. 1, No. 2, 2008

Abstract: This paper compares a select number of Value-at-Risk (VaR) models using daily data from the London stock exchange for estimating the model-based VaR. The period covers volatile market conditions triggered by a host of events that induced market uncertainty. Our results provide an indication of the degree of accuracy of the various methods and discuss issues of model selection. The empirical findings suggest that the Equally Weighted Moving Average (EWMA) model can furnish more accurate estimated VaR than the GARCH methods, including the popular Historical Simulation (HS) approach, by altering the estimation horizon.

Online publication date: Wed, 02-Jul-2008

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Monetary Economics and Finance (IJMEF):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com