Economics at your fingertips  

Comparing Value-at-Risk Methodologies

Luiz Lima () and Breno Pinheiro Néri ()
Additional contact information
Breno Pinheiro Néri: Graduate School of Economics Getúlio Vargas Foundation

Authors registered in the RePEc Author Service: Breno Pinheiro Neri ()

No 1, Computing in Economics and Finance 2006 from Society for Computational Economics

Abstract: We perform a Monte Carlo experimet to compare four different Value-at-Risk methodologies, RiskMetrics, Gaussian GARCH(1,1), Generalized Student-t APARCH(1,1), and ARCH(1) Quantile, under five different data generating processes. The ARCH(1) Quantile methodology does not assume any distribution for the returns, and this robustness is shown to avoid trajectories with too many violations. The number of violations tends to be higher in the non-robust methodologies when the distribution differs from the Gaussian one. We also perform an empirical exercise applying the four Value-at-Risk methodologies to daily return of the IBOVESPA (measured in dollar values) in a period of market turmoil (1996-2000), when happens the Korean crisis, the Russian crisis and the blast of the technology-stock market bubble. We display that, again, the ARCH(1) Quantile methodology dominates the non-robust methodologies, in the sense that it presents the least number of violations

Keywords: ARCH; Quantile; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C52 C53 (search for similar items in EconPapers)
Date: 2006-07-04
New Economics Papers: this item is included in nep-fmk, nep-ias and nep-rmg
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link) main text (text/plain)
Our link check indicates that this URL is bad, the error code is: 500 Status read failed: An existing connection was forcibly closed by the remote host.

Related works:
Journal Article: Comparing Value-at-Risk Methodologies (2007) Downloads
Working Paper: Comparing value-at-risk methodologies (2006) Downloads
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:

Access Statistics for this paper

More papers in Computing in Economics and Finance 2006 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().

Page updated 2024-07-19
Handle: RePEc:sce:scecfa:1