Value at risk calculation through ARCH factor methodology: Proposal and comparative analysis

In this paper we put forward a new method to estimate value at risk (VaR), autoregressive conditional heteroskedastic (ARCH) factor, which combines multivariate analysis with ARCH models. Firstly, from a set of correlated portfolio risk factors, we derive a smaller uncorrelated risk factors set, by...

Full description

Saved in:
Bibliographic Details
Published in:European journal of operational research 2003-11, Vol.150 (3), p.516-528
Main Authors: Cabedo Semper, J.David, Moya Clemente, Ismael
Format: Article
Language:English
Subjects:
ARCH models
Comparative analysis
Estimating techniques
Factor analysis
Financial modelling
Mathematical models
Multivariate analysis
Regression analysis
Risk
Studies
Valuation
Value at risk
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper we put forward a new method to estimate value at risk (VaR), autoregressive conditional heteroskedastic (ARCH) factor, which combines multivariate analysis with ARCH models. Firstly, from a set of correlated portfolio risk factors, we derive a smaller uncorrelated risk factors set, by applying multivariate analysis. Secondly, we use ARCH schemes to model uncorrelated factors historical behaviour. Thirdly, we use the estimated models to predict future values for factors standard deviation. From them, VaR calculation is immediate. In this way, ARCH factor methodology overcomes the multivariate ARCH models drawbacks, which, in practice, make these unworkable for VaR calculation purposes. We apply the proposed methodology over a set of foreign exchange risk exposed portfolios, obtaining better results than those reached when J.P. Morgan’s Riskmetrics is used.
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(02)00776-2