Value-at-Risk and Extreme Returns
Jon Danielsson () and
Casper de Vries ()
Annals of Economics and Statistics, 2000, issue 60, 239-270
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.
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Working Paper: Value-at-Risk and Extreme Returns (1998)
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Persistent link: https://EconPapers.repec.org/RePEc:adr:anecst:y:2000:i:60:p:239-270
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