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Large Sample Behavior of the CTE and VaR Estimators under Importance Sampling
Journal article   Peer reviewed

Large Sample Behavior of the CTE and VaR Estimators under Importance Sampling

Jae Youn Ahn and Nariankadu D Shyamalkumar
North American Actuarial Journal, Vol.15(3), pp.393-416
2011
DOI: 10.1080/10920277.2011.10597627

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Abstract

Abstract The α-level value at risk (Var) and the α-level conditional tail expectation (CTE) of a continuous random variable X are defined as its α-level quantile (denoted by qα ) and its conditional expectation given the event {X > qα }, respectively. Var is a popular risk measure in the banking sector, for both external and internal reporting purposes, while the CTE has recently become the risk measure of choice for insurance regulation in North America. Estimation of the CTE for company assets and liabilities is becoming an important actuarial exercise, and the size and complexity of these liabilities make inference procedures with good small sample performance very desirable. A common situation is one in which the CTE of the portfolio loss is estimated using simulated values, and in such situations use of variance reduction techniques such as importance sampling have proved to be fruitful. Construction of confidence intervals for the CTE relies on the availability of the asymptotic distribution of the ...

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