Probabilistic Constrained Optimization

Methodology and Applications

  • Stanislav P. Uryasev

Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 49)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Yu. Ermoliev, S. Uryasev, J. Wessels
    Pages 45-66
  3. Alexandr N. Golodnikov, Pavel S. Knopov, Panos M. Pardalos, Stanislav P. Uryasev
    Pages 102-131
  4. Alexander G. Kukush, Dmitrii S. Silvestrov
    Pages 173-185
  5. Helmut Mausser, Dan Rosen
    Pages 198-219
  6. Michael R. Murr, András Prékopa
    Pages 252-271

About this book

Introduction

Probabilistic and percentile/quantile functions play an important role in several applications, such as finance (Value-at-Risk), nuclear safety, and the environment. Recently, significant advances have been made in sensitivity analysis and optimization of probabilistic functions, which is the basis for construction of new efficient approaches. This book presents the state of the art in the theory of optimization of probabilistic functions and several engineering and finance applications, including material flow systems, production planning, Value-at-Risk, asset and liability management, and optimal trading strategies for financial derivatives (options).
Audience: The book is a valuable source of information for faculty, students, researchers, and practitioners in financial engineering, operation research, optimization, computer science, and related areas.

Keywords

Computer Finance Multimedia Options Simulation Stochastic Optimization calculus computer science model optimization programming

Editors and affiliations

  • Stanislav P. Uryasev
    • 1
  1. 1.University of FloridaGainesvilleUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-3150-7
  • Copyright Information Springer-Verlag US 2000
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-4840-3
  • Online ISBN 978-1-4757-3150-7
  • Series Print ISSN 1571-568X
  • About this book