© 2002

Stochastic Modeling in Economics and Finance


Part of the Applied Optimization book series (APOP, volume 75)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Pages 1-102
  3. Back Matter
    Pages 369-386

About this book


In Part I, the fundamentals of financial thinking and elementary mathematical methods of finance are presented. The method of presentation is simple enough to bridge the elements of financial arithmetic and complex models of financial math developed in the later parts. It covers characteristics of cash flows, yield curves, and valuation of securities.
Part II is devoted to the allocation of funds and risk management: classics (Markowitz theory of portfolio), capital asset pricing model, arbitrage pricing theory, asset & liability management, value at risk. The method explanation takes into account the computational aspects.
Part III explains modeling aspects of multistage stochastic programming on a relatively accessible level. It includes a survey of existing software, links to parametric, multiobjective and dynamic programming, and to probability and statistics. It focuses on scenario-based problems with the problems of scenario generation and output analysis discussed in detail and illustrated within a case study.


Arbitrage Finance Funds Martingale Stochastic Programming Stochastic calculus Stochastic model Variance calculus cash flow econometrics modeling operations research planning statistics

Authors and affiliations

  1. 1.Department of Probability and Mathematical Statistics, Faculty of Mathematics and PhysicsCharles UniversityPrague

Bibliographic information

Industry Sectors
Finance, Business & Banking


From the reviews:

"The monograph presents a complete overview on stochastic modeling in finance and economics. … the mathematical approach is accessible to a wide audience. … A comprehensive bibliography and index complete the book. The volume can be used in introductory graduate courses, and as a reference text for researchers in probability, statistics and operations research … ." (Emilia Di Lorenzo, Zentralblatt MATH, Vol. 1094 (20), 2006)