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Value-at-risk and extreme returns

By Jon Danielsson and C. G. de Vries


We propose a semi-parametric method for unconditional Value-at-Risk (VaR) evaluation. The largest risks are modelled parametrically, while smaller risks are captured by the non-parametric empirical distribution function. A comparison of methods on a portfolio of stock and option returns reveals that at the 5% level the RiskMetrics analysis is best, but for predictions of low probability worst outcomes, it strongly underpredicts the VaR while the semi-parametric method is the most accurate

Topics: HG Finance
Publisher: Institut National de la Statistique et des Etudes Economiques
Year: 2000
OAI identifier: oai:eprints.lse.ac.uk:7328
Provided by: LSE Research Online
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