1.

Record Nr.

UNINA9910709522903321

Titolo

Household weights and measures / / National Bureau of Standards

Pubbl/distr/stampa

Gaithersburg, MD : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , 1978

Descrizione fisica

1 online resource

Collana

NBS special publication ; ; 430

Soggetti

Metric system

Weights and measures - United States

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

1978.

Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes.

Title from PDF title page.

Nota di bibliografia

Includes bibliographical references.



2.

Record Nr.

UNINA9910795675103321

Autore

Brotons Martínez José Manuel

Titolo

La valoración financiera en el PGC / / José Manuel Brotons Martínez

Pubbl/distr/stampa

Elche : , : Universidad Miguel Hernández, , 2016

ISBN

9788416024285

Descrizione fisica

1 online resource (212 pages)

Disciplina

332

Soggetti

Finance

Lingua di pubblicazione

Spagnolo

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

3.

Record Nr.

UNINA9910973050003321

Autore

Rustem Berc

Titolo

Algorithms for worst-case design and applications to risk management / / Berc Rustem, Melendres Howe

Pubbl/distr/stampa

Princeton, N.J. ; ; Oxford, : Princeton University Press, 2002

ISBN

9786612157196

9781680158960

1680158961

9781282157194

1282157191

9781400825110

1400825113

9781400814602

140081460X

Edizione

[Course Book]

Descrizione fisica

1 online resource (405 p.)

Altri autori (Persone)

HoweMelendres

Disciplina

511.8

Soggetti

Risk management - Mathematical models

Risk - Mathematical models

Decision making - Mathematical models

Algorithms



Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Front matter -- Contents -- Preface -- Chapter 1. Introduction to Minimax -- Chapter 2. A Survey Of Continuous Minimax Algorithms -- Chapter 3. Algorithms For Computing Saddle Points -- Chapter 4. A Quasi-Newton Algorithm For Continuous Minimax -- Chapter 5. Numerical Experiments With Continuous Minimax Algorithms -- Chapter 6 Minimax As A Robust Strategy For Discrete Rival Scenarios -- Chapter 7 Discrete Minimax Algorithm For Equality And Inequality Constrained Models -- Chapter 8. A Continuous Minimax Strategy For Options Hedging -- Chapter 9. Minimax and Asset Allocation Problems -- Chapter 10. Asset/Liability Management Under Uncertainty -- Chapter 11 Robust Currency Management -- Index

Sommario/riassunto

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.