A Bayesian Confidence Interval for Value-at-Risk

Patricio Contreras and Stephen Satchell

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: This study assesses the accuracy of the value-at-risk estimate (VaR). On the basis of posterior distributions of the unknown population parameters, we develop a confidence interval for VaR that reflects the genuine information available about the portfolios for which the VaR is calculated. This approach is more accurate than that in Dowd (2000) as it avoids explaining the behaviour of the population parameters on the basis of distributions of sample parameters. We find that the accuracy of both the confidence interval and the VaR estimate depend more dramatically on the sample size than what Dowd’s results suggest. In addition, we not only find that the impact of the confidence level and the holding period at which the VaR is predicated are negligible compared to that of the sample size (as in Dowd), but also that the confidence interval is far from being symmetric.

Keywords: Bayesian Statistics; Confidence Interval; Monte Carlo Simulations; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C15 G00 (search for similar items in EconPapers)
Pages: 23
Date: 2003-11
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-fin and nep-rmg
Note: EM
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:0348

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