Comparing Value-at-Risk Methodologies

Luiz Lima () and Breno Pinheiro Néri ()
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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
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Citations: View citations in EconPapers (6)

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