CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles
Robert Engle and
Simone Manganelli
No 841, Econometric Society World Congress 2000 Contributed Papers from Econometric Society
Abstract:
Value at Risk has become the standard measure of market risk employed by financial institutions for both internal and regulatory purposes. Despite its conceptual simplicity, its measurement is a very challenging statistical problem and none of the methodologies developed so far give satisfactory solutions. Interpreting Value at Risk as a quantile of future portfolio values conditional on current information, we propose a new approach to quantile estimation that does not require any of the extreme assumptions invoked by existing methodologies (such as normality or i.i.d. returns). The Conditional Value at Risk or CAViaR model moves the focus of attention from the distribution of returns directly to the behavior of the quantile. Utilizing the criterion from Regression Quantiles, and postulating a variety of dynamic updating processes we propose methods based on a Genetic Algorithm to estimate the unknown parameters of CAViaR models. We propose a Dynamic Quantile Test of model adequacy that tests the hypothesis that in each period the probability of exceeding the VaR must be independent of all the past information. Applications to simulated and real data provide empirical support to our methodology and illustrate the ability of these algorithms to adapt to new risk environments.
Date: 2000-08-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (47)
Downloads: (external link)
http://fmwww.bc.edu/RePEc/es2000/0841.pdf main text (application/pdf)
Related works:
Journal Article: CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles (2004) 
Working Paper: CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles (1999) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ecm:wc2000:0841
Access Statistics for this paper
More papers in Econometric Society World Congress 2000 Contributed Papers from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().