ALGORITHMS FOR WORST-CASE DESIGN AND APPLICATIONS TO RISK MANAGEMENT
Language: English
Published by Princeton University Press, Princeton, 2002
- First Edition
- Hardcover
- Used

Seller: Second Story Books, ABAA, Rockville, MD, U.S.A.Second Story Books, ABAA
AbeBooks seller since May 29, 1997
Condition: Used
US$ 26.25
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Add to basketItem description from seller
Octavo, xi, xv, 389 pages. In Very Good condition with a Very Good minus dust jacket. Spine pictorial gray/pink with red and white lettering. Exterior has slight shelf wear including few scratches/scuffs and slight edge wear. Previous bookshop's sticker to the rear. Boards have minimal wear. Text block has very faint wear to the edges. Illustrated. First edition, first printing. NOTE: Shelved in Netdesk Column M, ND-M. 1385268. FP New Rockville Stock.
Seller Inventory # 1385268
- Title
- ALGORITHMS FOR WORST-CASE DESIGN AND APPLICATIONS TO RISK MANAGEMENT
- Author
- Rustem, Berç and Howe, Melendres
- Publisher
- Princeton University Press, Princeton
- Publication year
- 2002
- Dust jacket
- Dust Jacket Included
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0691091544
- ISBN 13
- 9780691091549
- Edition
- First Edition, First Printing.
- Seller catalogs
- Social Sciences
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.
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About the Author
"About the title" may belong to another edition of this title.
Second Story Books, ABAA
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