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Könyv Algorithms for Worst-Case Design and Applications to Risk Management Berc Rustem

Algorithms for Worst-Case Design and Applications to Risk Management

Szerző: Berc Rustem, Melendres Howe
Nyelv: Angol
Kötés: Kemény kötésű
Kiadó: Princeton University Press
Elérhetőség: Beszállítói készleten
Küldés 14-21 napon belül
75 459 Ft
Recognizing that robust decision making is vital in risk management, this book provides concepts and...

Információk a könyvről

Szerző
Berc Rustem, Melendres Howe
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2002
oldal
408
EAN
9780691091549
ISBN
0691091544
Enbook ID
04640434
Kiadó
Princeton University Press
Súly
482
Méretek
152 x 235 x 28

Teljes leírás

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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