A measure-valued differentiation approach to sensitivities of quantiles

B.F. Heidergott, W. Volk-Makarewicz

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Quantiles play an important role in modelling quality of service in the service industry and in modelling risk in the financial industry. The recent discovery that efficient simulation-based estimators can be obtained for quantile sensitivities has led to an intensive search for sample-path differentiation-based estimators for quantile sensitivities. In this paper, we present a novel approach to quantile sensitivity estimation. Our approach elaborates on the concept of measure-valued differentiation. Thereby, we overcome the main obstacle of the sample-path approach, which is the requirement that the sample cost have to be Lipschitz continuous with respect to the parameter of interest. Specifically, we perform a sensitivity analysis of the value at risk in financial models. In addition, we discuss an application of our sensitivity estimator to queueing networks.
Original languageEnglish
Pages (from-to)293-317
JournalMathematics of Operations Research
Volume41
Issue number1
DOIs
Publication statusPublished - 2016

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Quantile
Queueing networks
Sample Path
Estimator
Sensitivity analysis
Industry
Quality of service
Value at Risk
Queueing Networks
Modeling
Quality of Service
Sensitivity Analysis
Lipschitz
Costs
Requirements
Simulation
Model

Cite this

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A measure-valued differentiation approach to sensitivities of quantiles. / Heidergott, B.F.; Volk-Makarewicz, W.

In: Mathematics of Operations Research, Vol. 41, No. 1, 2016, p. 293-317.

Research output: Contribution to JournalArticleAcademicpeer-review

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