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Risk Management, Mathematical Analysis - General & Miscellaneous, Mathematical Programming & Operations Research, Mathematical Modeling - Economics
Algorithms for Worst-Case Design and Applications to Risk Management by Berc Rustem — book cover

Algorithms for Worst-Case Design and Applications to Risk Management

by Berc Rustem, Melendres Howe
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Overview

Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making.

Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous—possibly infinite—and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions—which also offer the possibility of multiple maxima—ensures this optimality.

Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values.

Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management.

Synopsis

Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making.Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous--possibly infinite--and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions--which also offer the possibility of multiple maxima--ensures this optimality.Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values.Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable topractitioners in risk management.

David G. Luenberger - Journal of Economic Dynamics & Control

This is minimax made practical, while maintaining theoretical rigor, computational feasibility, and good problem formulation. . . . The book is very comprehensive, and in many places quite detailed. However, it is easy to find a path through the material suited to one's purpose, ranging from a quick overview of this powerful approach to a detailed study of it and the relevant background material. It is an excellent example of how the results of an extensive research program can be translated into a book that is accessible and which is likely to have significant impact in both the optimization and finance communities.

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Editorials

Journal of Economics

This book will be very helpful to those interested in uncertainty and robust decisions. I recommend it warmly to all practitioners and researchers in economics, environment, engineering design, finance and operations research.
— P.M. Pardalos

Journal of Economic Dynamics & Control

This is minimax made practical, while maintaining theoretical rigor, computational feasibility, and good problem formulation. . . . The book is very comprehensive, and in many places quite detailed. However, it is easy to find a path through the material suited to one's purpose, ranging from a quick overview of this powerful approach to a detailed study of it and the relevant background material. It is an excellent example of how the results of an extensive research program can be translated into a book that is accessible and which is likely to have significant impact in both the optimization and finance communities.
— David G. Luenberger

Zentralblatt MATH Database

Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management.

Zentralblatt MATH


Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management.

Journal of Economics - P.M. Pardalos

This book will be very helpful to those interested in uncertainty and robust decisions. I recommend it warmly to all practitioners and researchers in economics, environment, engineering design, finance and operations research.

Journal of Economic Dynamics & Control - David G. Luenberger

This is minimax made practical, while maintaining theoretical rigor, computational feasibility, and good problem formulation. . . . The book is very comprehensive, and in many places quite detailed. However, it is easy to find a path through the material suited to one's purpose, ranging from a quick overview of this powerful approach to a detailed study of it and the relevant background material. It is an excellent example of how the results of an extensive research program can be translated into a book that is accessible and which is likely to have significant impact in both the optimization and finance communities.

Book Details

Published
August 1, 2002
Publisher
Princeton University Press
Pages
408
Format
Hardcover
ISBN
9780691091549

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