Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Algorithms for Worst-Case Design and Applications to Risk Management

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Berc Rustem 作者
Princeton University Press
譯者
2002-08-26 出版日期
408 頁數
USD 90.00 價格
Hardcover
叢書系列
9780691091549 圖書編碼

Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 圖書標籤: risk  minmax  management  application  Mathematics   


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Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Algorithms for Worst-Case Design and Applications to Risk Management 在線電子書 圖書描述

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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