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Expected shortfall in credit portfolios with extremal dependence

Published: 04 December 2005 Publication History

Abstract

We consider the risk of a portfolio comprised of loans, bonds, and financial instruments that are subject to possible default. We are interested in efficiently estimating expected excess loss conditioned on the event that the portfolio incurs large losses over a fixed time horizon; this risk measure is often referred to as expected shortfall. We consider a heterogeneous mix of obligors and assume a portfolio dependence structure that supports extremal dependence among obligors and does not hinge solely on correlation. We first derive sharp asymptotics that illustrate the implications of extremal dependence among obligors in the risk of the portfolio. Using this as a stepping stone, we develop a multi-stage importance sampling algorithm that is shown to have bounded relative error in estimating expected shortfall.

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Cited By

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  • (2021)Efficient black-box importance sampling for VaR and CVaR estimationProceedings of the Winter Simulation Conference10.5555/3522802.3522952(1-12)Online publication date: 13-Dec-2021
  • (2006)Computing worst-case tail probabilities in credit riskProceedings of the 38th conference on Winter simulation10.5555/1218112.1218162(246-254)Online publication date: 3-Dec-2006
  1. Expected shortfall in credit portfolios with extremal dependence

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    cover image ACM Conferences
    WSC '05: Proceedings of the 37th conference on Winter simulation
    December 2005
    2769 pages
    ISBN:0780395190

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    Published: 04 December 2005

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    WSC '05 Paper Acceptance Rate 209 of 316 submissions, 66%;
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    • (2021)Efficient black-box importance sampling for VaR and CVaR estimationProceedings of the Winter Simulation Conference10.5555/3522802.3522952(1-12)Online publication date: 13-Dec-2021
    • (2006)Computing worst-case tail probabilities in credit riskProceedings of the 38th conference on Winter simulation10.5555/1218112.1218162(246-254)Online publication date: 3-Dec-2006

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