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Algorithms for worst-case design and applications to risk management

Author: Berc Rustem; Melendres Howe
Publisher: Princeton, N.J. ; Oxford : Princeton University Press, ©2002.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Rustem, Berc.
Algorithms for worst-case design and applications to risk management.
Princeton, N.J. ; Oxford : Princeton University Press, ©2002
(OCoLC)48931090
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Berc Rustem; Melendres Howe
ISBN: 140081460X 9781400814602 9781400825110 1400825113 9781680158960 1680158961
OCLC Number: 52243294
Description: 1 online resource (xv, 389 pages)
Contents: Contents; Preface; Chapter 1. Introduction to minimax; Chapter 2. A survey of continuous minimax algorithms; Chapter 3. Algorithms for computing saddle points; Chapter 4. A quasi-Newton algorithm for continuous minimax; Chapter 5. Numerical experiments with continuous minimax algorithms; Chapter 6. Minimax as a robust strategy for discrete rival scenarios; Chapter 7. Discrete minimax algorithm for nonlinear equality and inequality constrained models; Chapter 8. A continuous minimax strategy for options hedging; Chapter 9. Minimax and asset allocation problems. Chapter 10. Asset/liability management under uncertaintyChapter 11. Robust currency management; Index.
Responsibility: Berç Rustem, Melendres Howe.
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Abstract:

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-

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