Applied Computational Economics and Finance

Applied Computational Economics and Finance
by Mario J. Miranda, Paul L. Fackler

Applied Computational Economics and Finance
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Book Summary Information

Author: Mario J. Miranda, Paul L. Fackler
Edition: Paperback
Audio: English (Unknown); English (Original Language); English (Published)
Published: 2002-09-01
ISBN: 0262633094
Number of pages: 528
Publisher: The MIT Press

Book Reviews of Applied Computational Economics and Finance

Book Review: Good but ...
Summary: 4 Stars

I was looking for a book that teaches how to use MATLAB to solve certain finance and economics problems, and purchased this book. The book covers very interesting topics and discusses many types of solution methods. However, the applications to MATLAB are not presented in a user-friendly way. In particular, they do not present things in a step-by-step manner and assume many things. The reader is then left to figure out how to complete programs either from some other part of the book or from prior knowledge. Thus, the book is successful in letting the reader become aware of the capabilities of MATLAB (i.e. what sort of computational techniques the program can do). However, it would havae been best if the authors wrote all the programs with complete codes. They often mention that the code assumes that the reader does this and does that.

Summary of Applied Computational Economics and Finance

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.

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