Algorithms For Worst-Case Design And Applications To Risk Management

Berç Rustem, Melendres Howe

404 pages, parution le 06/12/2002

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Résumé

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.

Contents

Introduction to Minimax
A Survey of Continuous Minimax Algorithms
Algorithms for Computing Saddle Points
A Quasi-Newton Algorithm For Continuous Minimax
Numerical Experiments With Continuous Minimax Algorithms
Minimax As a Robust Strategy for Discrete Rival Scenarios
Discrete Minimax Algortihm For Nonlinear Equality and Inequality Constrained Models
A Continuous Minimax Strategy For Options Hedging
Minimax And Asset Allocation Problems
Asset/Liability Management Under Uncertainty
Robust Currency Management

L'auteur - Berç Rustem

Berç Rustem is Professor of Computational Methods in Operations Research at the Imperial College of Science, Technology, and Medicine, London, and the author of Projection Methods in Constrained Optimisation and Applications to Optimal Policy Decisions and Algorithms for Nonlinear Programming and Multiple-Objective Decisions.

L'auteur - Melendres Howe

Melendres Howe, a doctoral graduate of Imperial College, is currently a Treasury Officer at the Asian Development Bank. Previously, she worked in the City of London, as Senior Analyst at a Nomura and Vice President (Currency) at JP Morgan.

Caractéristiques techniques

	PAPIER
Éditeur(s)	Princeton University Press
Auteur(s)	Berç Rustem, Melendres Howe
Parution	06/12/2002
Nb. de pages	404
Format	16,3 x 24
Couverture	Relié
Poids	735g
Intérieur	Noir et Blanc
EAN13	9780691091549
ISBN13	978-0-691-09154-9