Stochastic Modeling in Economics and Finance / Edition 1

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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.
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Editorial Reviews

From the Publisher

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)

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Product Details

  • ISBN-13: 9781441952318
  • Publisher: Springer US
  • Publication date: 12/7/2010
  • Series: Applied Optimization Series, #75
  • Edition description: Softcover reprint of hardcover 1st ed. 2002
  • Edition number: 1
  • Pages: 386
  • Product dimensions: 0.82 (w) x 9.21 (h) x 6.14 (d)

Table of Contents

Preface. Acknowledgments. Part I: Fundamentals. I.1. Money, Capital, and Securities. I.2. Interest Rate. I.3. Measures of Cash Flows. I.4. Return, Expected Return, and Risk. I.5. Valuation of Securities. I.6. Matching of Assets and Liabilities. I.7. Index Numbers and Inflation. I.8. Basics of Utility Theory. I.9. Markowitz Mean-Variance Portfolio. I.10. Capital Asset Pricing Model. I.11. Arbitrage Pricing Theory. I.12. Bibliographical Notes. Part II: Discrete Time Stochastic Decision Models. II.1. Introduction and Preliminaries. II.2. Multistage Stochastic Programs. II.3. Multiple Criteria. II.4. Selected Applications in Finance and Economics. II.5. Approximation Via Scenarios. II.6. Case Study: Bond Portfolio Management Problem. II.7. Incomplete Input Information. II.8. Numerical Techniques and Available Software; P. Popela. II.9. Bibliographical Notes. Part III: Stochastic Analysis and Diffusion Finance. III.1. Martingales. III.2. Stochastic Integration. III.3. Diffusion Financial Mathematics. III.4. Bibliographical Notes. References. Index.
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