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Quantifying and Correcting the Bias in Estimated Risk Measures

Published online by Cambridge University Press:  17 April 2015

Joseph Hyun Tae Kim  and
Mary R. Hardy
Joseph Hyun Tae Kim
Affiliation:
Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, Canada
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Abstract

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In this paper we explore the bias in the estimation of the Value at Risk and Conditional Tail Expectation risk measures using Monte Carlo simulation. We assess the use of bootstrap techniques to correct the bias for a number of different examples. In the case of the Conditional Tail Expectation, we show that application of the exact bootstrap can improve estimates, and we develop a practical guideline for assessing when to use the exact bootstrap.

Type
Articles
Information
ASTIN Bulletin: The Journal of the IAA , Volume 37 , Issue 2 , November 2007 , pp. 365 - 386
Copyright
Copyright © ASTIN Bulletin 2007

Footnotes

*

Joseph Kim acknowledges the support in part of the Ph.D. Grant of the Society of Actuaries and the PGS-D2 grant of the Natural Sciences and Engineering Research Council of Canada.

§

Mary Hardy acknowledges the support of the Natural Sciences and Engineering Research Council of Canada.

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