Programming Languages And Systems In Computational Economics And Finance

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.

The developments within the computationally and numerically oriented areas of Operations Research, Finance, Statistics and Economics have been significant 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 invited, peer-reviewed 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 wide range of relevant topics; Models and Modelling in Operations Research and Economic (Matt Saltzman; Pere Gomis-Porqueras and Alex Haro; Jerome Kruiser; Don Shobrys), novel High-level and Object-Oriented approaches to programming (Jurgen Doornik; Chris Birchenhall; Christopher Baum; Tim Hultberg), through advanced uses of Maple and MATLAB (Des Higham and Peter Kloeden; Ric Herbert, Jerzy Ombach and Jolanta Jarnicka; George Lindfield and John Penny), and applications and solution of Differential Equations in Finance (Peter Honoré and Rolf Poulsen; Jens Hugger; Sasha Cyganowski and Lars GrÃ1⁄4ne). Each article is written from a personal, explorative perspective that invites the reader to discover new approaches to solving old problems. In the longer run it is hoped that this volume will facilitate cross-fertilization among the computational fields.

Introduction to Computational Economics Using Fortran is the essential guide to conducting economic research on a computer. Aimed at students of all levels of education as well as advanced economic researchers, it facilitates the first steps into writing programs using Fortran. Introduction to Computational Economics Using Fortran assumes no prior experience as it introduces the reader to this programming language. It shows the reader how to apply the most important numerical methods conducted by computational economists using the toolbox that accompanies this text. It offers various examples from economics and finance organized in self-contained chapters that speak to a diverse range of levels and academic backgrounds. Each topic is supported by an explanation of the theoretical background, a demonstration of how to implement the problem on the computer, and a discussion of simulation results. Readers can work through various exercises that promote practical experience and deepen their economic and technical insights. This textbook is accompanied by a website from which readers can download all program codes as well as a numerical toolbox, and receive technical information on how to install Fortran on their computer.

This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses. The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and resource economics, macroeconomics, and finance. The book also provides an extensive Web-site library of computer utilities and demonstration programs. The book is divided into two parts. The first part develops basic numerical methods, including linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation. The second part presents methods for solving dynamic stochastic models in economics and finance, including dynamic programming, rational expectations, and arbitrage pricing models in discrete and continuous time. The book uses MATLAB to illustrate the algorithms and includes a utilities toolbox to help readers develop their own computational economics applications.

Econometric techniques and models are still being extensively used in the business of forecasting and policy advice. This book presents recent advances in the theory and applications of quantitative economic policy, with particular emphasis on fiscal and monetary policies in a European and global context. The volume honors Andrew Hughes Hallett, a pioneer and major scientist in quantitative economic policy analysis, whose contributors are among his friends and former students.

This publication contains a substantial amount of detail about the broad history of the development of econometric software based on the personal recollections of many people. For economists, the computer has increasingly become the primary applied research tool, and it is software that makes the computer work.

This collection of articles is edited by Hal Varian, Dean of the School of Information Management and Systems, University of California, Berkeley. It provides a high quality and practical selection of contributed articles that impart the expertise of an international contingent of Mathematica users from the economic, financial, investments, quantitative business and operations research communities.

Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.

Tools for Computational Finance offers a clear explanation of computational issues arising in financial mathematics. The new third edition is thoroughly revised and significantly extended, including an extensive new section on analytic methods, focused mainly on interpolation approach and quadratic approximation. Other new material is devoted to risk-neutrality, early-exercise curves, multidimensional Black-Scholes models, the integral representation of options and the derivation of the Black-Scholes equation. New figures, more exercises, and expanded background material make this guide a real must-to-have for everyone working in the world of financial engineering.

Following theseminal Palgrave Handbook of Econometrics: Volume I , this second volume brings together the finestacademicsworking in econometrics today andexploresapplied econometrics, containing contributions onsubjects includinggrowth/development econometrics and applied econometrics and computing.