An empirical comparison of alternative models in estimating value at risk: evidence and application from the LSE

Everton Dockery, M. Efentakis

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)201-218
Number of pages18
JournalInternational Journal of Financial Economics and Econometrics
Volume1
Issue number2
Publication statusPublished - 2008

Fingerprint

Dive into the research topics of 'An empirical comparison of alternative models in estimating value at risk: evidence and application from the LSE'. Together they form a unique fingerprint.

Cite this