Algorithms for Worst-Case Design and Applications to Risk Management
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A01=Berc Rustem
A01=Melendres Howe
Accuracy and precision
Algorithm
Algorithmic trading
Asset allocation
Asset management
At Best
Author_Berc Rustem
Author_Melendres Howe
Basis risk
Benchmarking
Calculation
Call option
Capital asset pricing model
Category=KJMD
Category=PBU
Category=PBW
Contingent liability
Covariance matrix
Currency
Currency overlay
Decision problem
Depreciation
Dirty price
Downside Deviation
Downside risk
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Exchange rate
Expected value
Forecast error
Forecasting
Foreign exchange risk
Future value
Hedge (finance)
Hedge Ratio
Implied volatility
Insurance
Interest rate
Interest Rate Sensitivity
Iteration
Liability Management
Libor
Loss function
Mathematical optimization
Mismatch
Nonlinear programming
Observational error
Optimization problem
Option (finance)
Option value (cost-benefit analysis)
Payment
Payout
Performance attribution
Portfolio manager
Prepayment Model
Probability
Probability of default
Risk aversion
Risk management
Risk management tools
Risk premium
Scenario optimization
Sensitivity analysis
Shortage
Shortfall
Standard deviation
Stochastic programming
Strike price
Subgradient method
Technical analysis
Tracking error
Trade-off
Transaction cost
Uncertainty
Variable (mathematics)
Yield curve
Yield Curve Risk
Product details
- ISBN 9780691091549
- Weight: 482g
- Dimensions: 152 x 235mm
- Publication Date: 15 Sep 2002
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Hardback
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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.
Berc 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". 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.
