How well do risk measurement models estimate VaR during good and bad times? Evidence from the Korean stock market
by Everton Dockery; Miltiadis Efentakis
International Journal of Financial Markets and Derivatives (IJFMD), Vol. 3, No. 2, 2013

Abstract: This paper presents empirical evidence on the performance of a number of selected risk measurement models for measuring the value-at-risk in the South Korean stock market with regard to their ability to consistently furnish accurate estimated VaR risk measure during good and bad times. The soundness of model performance in the accuracy of estimated VaRs are compared using risk management loss function and likelihood ratio tests for coverage probability to ascertain which of the models can accurately capture market risk over varying market conditions. The results indicate that the Equally Weighted Moving Average model and the RiskMetrics model captures and thus furnish unsteady but accurate estimated VaRs of the index return series, especially during crisis periods. The findings also demonstrate that these models can deliver more accurate estimated VaRs than the widely employed GARCH and historical simulation specifications.

Online publication date: Fri, 25-Jul-2014

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 Financial Markets and Derivatives (IJFMD):
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