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Model Risk Management : Risk Bounds under Uncertainty by Ludger Rüschendorf, Steven Vanduffel and Carole Bernard (2024, Hardcover)

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About this product

Product Identifiers

PublisherCambridge University Press

ISBN-101009367161

ISBN-139781009367165

eBay Product ID (ePID)25061934019

Product Key Features

Number of Pages344 Pages

Publication NameModel Risk Management : Risk Bounds under Uncertainty

LanguageEnglish

Publication Year2024

SubjectOptimization

TypeTextbook

AuthorLudger Rüschendorf, Steven Vanduffel, Carole Bernard

Subject AreaMathematics

FormatHardcover

Dimensions

Item Height0.9 in

Item Length9.9 in

Item Width6.9 in

Additional Product Features

LCCN2023-032170

Dewey Edition23

Reviews'Written by three of the foremost experts in the field, Model Risk Management is the definitive textbook on bounding aggregate or portfolio risks in the face of partial information about their probabilistic structure, a problem that has applications in many areas of financial risk management, and beyond.' Alexander McNeil, University of York

IllustratedYes

Dewey Decimal658.1552

Table Of ContentIntroduction; Part I. Risk Bounds for Portfolios Based on Marginal Information: 1. Risk bounds with known marginal distributions; 2. Rearrangement algorithm; 3. Dual bounds; 4. Asymptotic equivalence results; Part II. Additional Dependence Constraints: 5. Improved standard bounds; 6. VaR bounds with variance constraints; 7. Distributions specified on a subset; Part III. Additional Information on the Structure: 8. Additional information on functionals of the risk vector; 9. Partially specified risk factor models; 10. Models with a specified subgroup structure; Part IV. Risk Bounds Under Moment Information: 11. Bounds on VaR, TVaR, and RVaR under moment information; 12. Bounds for distortion risk measures under moment information; 13. Bounds for VaR, TVaR, and RVaR under unimodality constraints; 14. Moment bounds in neighborhood models; References; Index.

SynopsisThis book provides the first systematic treatment of model risk, outlining the tools needed to quantify model uncertainty, to study its effects, and, in particular, to determine the best upper and lower risk bounds for various risk aggregation functionals of interest. Drawing on both numerical and analytical examples, this is a thorough reference work for actuaries, risk managers, and regulators. Supervisory authorities can use the methods discussed to challenge the models used by banks and insurers, and banks and insurers can use them to prioritize the activities on model development, identifying which ones require more attention than others. In sum, it is essential reading for all those working in portfolio theory and the theory of financial and engineering risk, as well as for practitioners in these areas. It can also be used as a textbook for graduate courses on risk bounds and model uncertainty., The first systematic treatment of model risk, this book provides the tools needed to quantify and assess the impact of model uncertainty. It will be essential for all those working in portfolio theory and the theory of financial and engineering risk, for practitioners in these areas, and for graduate courses on risk bounds and model uncertainty.

LC Classification NumberHD61.R867 2023