12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

97%

97% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > A study of Value-at-Risk based on M-estimators ...
View graph of relations

« Back

A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models

Research output: Contribution to journalJournal article

Published

<mark>Journal publication date</mark>08/2012
<mark>Journal</mark>Journal of Forecasting
Issue5
Volume31
Number of pages14
Pages377-390
Early online date26/02/11
<mark>Original language</mark>English

Abstract

In this paper, we investigate the performance of a class of M-estimators for both
symmetric and asymmetric conditional heteroscedastic models in the prediction
of value-at-risk. The class of estimators includes the least absolute deviation
(LAD), Huber’s, Cauchy and B-estimator, as well as the well-known quasi
maximum likelihood estimator (QMLE). We use a wide range of summary
statistics to compare both the in-sample and out-of-sample VaR estimates of
three well-known stock indices. Our empirical study suggests that in general
Cauchy, Huber and B-estimator have better performance in predicting one-step ahead VaR than the commonly used QMLE.