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Using Order Statistics to Estimate Confidence Intervals for Probabilistic Risk Measures

Kevin Dowd
The Journal of Derivatives Winter 2006, 14 (2) 77-81; DOI: https://doi.org/10.3905/jod.2006.667552
Kevin Dowd
A professor of financial risk management in the Centre for Risk and Insurance Studies at Nottingham University Business School in Nottingham, UK.
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  • For correspondence: kevin.dowd@nottingham.ac.uk
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Abstract

Value at Risk (VaR) and related probabilistic risk measures have become ubiquitous in the realm of risk management. But any statistician knows that a point estimate is only part of what one needs to know, the other being a measure of confidence about that estimate. In this article, Dowd provides an easy way to estimate such confidence intervals using the theory of order statistics. The procedure is straightforward, nearly instantaneous to execute, and can be used with any parametric or non-parametric returns distribution.

TOPICS: Derivatives, VAR and use of alternative risk measures of trading risk

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The Journal of Derivatives
Vol. 14, Issue 2
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Using Order Statistics to Estimate Confidence Intervals for Probabilistic Risk Measures
Kevin Dowd
The Journal of Derivatives Nov 2006, 14 (2) 77-81; DOI: 10.3905/jod.2006.667552

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Using Order Statistics to Estimate Confidence Intervals for Probabilistic Risk Measures
Kevin Dowd
The Journal of Derivatives Nov 2006, 14 (2) 77-81; DOI: 10.3905/jod.2006.667552
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