Programming Languages and Systems in Computational Economics and Finance

1. Front Matter

   Pages i-xii

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2. Models and Modelling

   1. Front Matter

      Pages 1-1

      PDF

   2. Coin-Or: An Open-Source Library for Optimization

      • Matthew J. Saltzman

      Pages 3-32

   3. Macroeconomics: What can we Learn from the Dynamical Systems Literature?

      • Pere Gomis-Porqueras, Àlex Haro

      Pages 33-61

   4. The Rapid Implementation of Asset/Liability Models for Sovereign Risk Management

      • Jerome L. Kreuser

      Pages 63-92

   5. Human and Organization Challenges to the Use of Optimization

      • Donald E. Shobrys

      Pages 93-112

3. High-Level and Object Oriented Approaches

   1. Front Matter

      Pages 113-113

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   2. Object-Oriented Programming in Econometrics and Statistics Using Ox: A Comparison with C++, Java and C#

      • Jurgen A. Doornik

      Pages 115-147

   3. Design Patterns in Hierarchical Models

      • Chris R. Birchenhall

      Pages 149-172

   4. Facilitating Applied Economic Research with Stata

      • Christopher F. Baum

      Pages 173-197

   5. Formulation of Linear Optimization Problems in C++

      • Tim H. Hultberg

      Pages 199-229

4. Maple and MATLAB

   1. Front Matter

      Pages 231-231

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   2. MAPLE and MATLAB for Stochastic Differential Equations in Finance

      • Desmond J. Higham, Peter E. Kloeden

      Pages 233-269

   3. Computational Programming Environments

      • Ric D. Herbert

      Pages 271-296

   4. Statistics and Simulations with MAPLE

      • Jerzy Ombach, Jolanta Jarnicka

      Pages 297-330

   5. MATLAB as a Flexible Tool for Data Analysis and Optimisation

      • George R. Lindfield, John E. T. Penny

      Pages 331-366

5. Options and Differential Equations

   1. Front Matter

      Pages 367-367

      PDF

   2. Option Pricing with Excel

      • Peter Honoré, Rolf Poulsen

      Pages 369-402

   3. Numerical Solution of Boundary Value Problems in Computational Finance

      • Jens Hugger

      Pages 403-439

   4. MAPLE for Jump—Diffusion Stochastic Differential Equations in Finance

      • Sasha Cyganowski, Lars Grüne, Peter E. Kloeden

      Pages 441-460

The developments within the computationally and numerically oriented ar­ eas of Operations Research, Finance, Statistics and Economics have been sig­ nificant over the past few decades. Each area has been developing its own computer systems and languages that suit its needs, but there is relatively little cross-fertilization among them yet. This volume contains a collection of papers that each highlights a particular system, language, model or paradigm from one of the computational disciplines, aimed at researchers and practitioners from the other fields. The 15 papers cover a number of relevant topics: Models and Modelling in Operations Research and Economics, novel High-level and Object-Oriented approaches to programming, through advanced uses of Maple and MATLAB, and applications and solution of Differential Equations in Finance. It is hoped that the material in this volume will whet the reader's appetite for discovering and exploring new approaches to old problems, and in the longer run facilitate cross-fertilization among the fields. We would like to thank the contributing authors, the reviewers, the publisher, and last, but not least, Jesper Saxtorph, Anders Nielsen, and Thomas Stidsen for invaluable technical assistance.

• Analysis
• Finance
• Stochastic Differential Equations
• computer
• linear optimization
• modeling
• operations research
• optimization
• programming
• programming language
• statistics

• Technical University of Denmark, Denmark

  Søren S. Nielsen

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