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Algorithms for worst-case design and applications to risk management / Berç Rustem, Melendres Howe.

By: Contributor(s): Material type: TextTextPublication details: Princeton, N.J. ; Oxford : Princeton University Press, ©2002.Description: 1 online resource (xv, 389 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 140081460X
  • 9781400814602
  • 9781400825110
  • 1400825113
  • 9781680158960
  • 1680158961
Subject(s): Genre/Form: Additional physical formats: Print version:: Algorithms for worst-case design and applications to risk management.DDC classification:
  • 511.8 21
LOC classification:
  • HD61 .R87 2002eb
Online resources:
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.
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 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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Includes bibliographical references and index.

Print version record.

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.

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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