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Comparing Value-at-Risk Methodologies

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  • Luiz Renato Lima
  • Breno Pinheiro Néri

    ()
    (Graduate School of Economics Getúlio Vargas Foundation)

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

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 1.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:1

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Keywords: ARCH Quantile Value-at-Risk;

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Cited by:
  1. Lima, Luiz Renato Regis de Oliveira & Sampaio, Raquel Menezes Bezerra & Gaglianone, Wagner Piazza, 2006. "Debt ceiling and fiscal sustainability in Brazil: a quantile autoregression approach," Economics Working Papers (Ensaios Economicos da EPGE) 631, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  2. Michael McAleer & David Allen & Ron Amram, 2011. "Volatility Spillovers from the Chinese Stock Market to Economic Neighbours," KIER Working Papers 805, Kyoto University, Institute of Economic Research.
  3. Gaglianone, Wagner Piazza & Linton, Oliver & Lima, Luiz Renato Regis de Oliveira, 2008. "Evaluating Value-at-Risk models via Quantile regressions," Economics Working Papers (Ensaios Economicos da EPGE) 679, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  4. David E. Allen & Michael McAleer & R.J. Powell & A.K. Singh, 2013. "Volatility Spillovers from the US to Australia and China across the GFC," Tinbergen Institute Discussion Papers 13-009/III, Tinbergen Institute, revised 01 Feb 2013.
  5. Aymen BEN REJEB & Ousama BEN SALHA & Jaleleddine BEN REJEB, 2012. "Value-at-Risk Analysis for the Tunisian Currency Market: A Comparative Study," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 110-125.
  6. Xiao, Zhijie & Lima, Luiz Renato Regis de Oliveira, 2006. "Testing Covariance Stationarity," Economics Working Papers (Ensaios Economicos da EPGE) 632, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  7. repec:ecu:wpaper:2010-03 is not listed on IDEAS

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