Asymptotic representations for importance-sampling estimators of value-at-risk and conditional value-at-risk

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)246-251
Journal / PublicationOperations Research Letters
Volume38
Issue number4
StatePublished - Jul 2010
Externally publishedYes

Abstract

Value-at-risk (VaR) and conditional value-at-risk (CVaR) are important risk measures. They are often estimated by using importance-sampling (IS) techniques. In this paper, we derive the asymptotic representations for IS estimators of VaR and CVaR. Based on these representations, we are able to prove the consistency and asymptotic normality of the estimators and to provide simple conditions under which the IS estimators have smaller asymptotic variances than the ordinary Monte Carlo estimators. © 2010 Elsevier B.V. All rights reserved.

Research Area(s)

  • Asymptotic representation, Conditional value-at-risk, Importance sampling, Value-at-risk