Neural Networks in Finance: Gaining Predictive Edge in the Market / Edition 1

Neural Networks in Finance: Gaining Predictive Edge in the Market / Edition 1

by Paul D. McNelis
     
 

[back jacket]

Business/Finance

Neural Networks in Finance
Gaining Predictive Edge in the Market

Paul McNelis

"This book clarifies many of the mysteries of Neural Networks and related optimization techniques for researchers in both economics and finance. It contains many practical examples backed up with computer programs for readers to explore. I

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Overview

[back jacket]

Business/Finance

Neural Networks in Finance
Gaining Predictive Edge in the Market

Paul McNelis

"This book clarifies many of the mysteries of Neural Networks and related optimization techniques for researchers in both economics and finance. It contains many practical examples backed up with computer programs for readers to explore. I recommend it to anyone who wants to understand methods used in nonlinear forecasting."
— Blake LeBaron, Professor of Finance, Brandeis University

"An important addition to the select collection of books on financial econometrics… Neural Networks in Finance serves as an important reference on neural network models of nonlinear dynamics as a practical econometric tool for better decision-making in financial markets."
— Roberto S. Mariano, Dean of School of Economics and Social Sciences & Vice-Provost for Research, Singapore Management University; Professor Emeritus of Economics, University of Pennsylvania

Neural Networks in Finance explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. The text shows that these networks are easy to implement and interpret once the time-honored quest for closed form solutions is reconsidered.

McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany, to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. Numerical illustrations use MATLAB code and the book is accompanied by a website.

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Product Details

ISBN-13:
9780124859678
Publisher:
Elsevier Science
Publication date:
01/05/2005
Series:
Academic Press Advanced Finance Series
Pages:
256
Product dimensions:
6.20(w) x 9.24(h) x 0.80(d)

Table of Contents

Preface; 1. Introduction; 2. What Are Neural Networks; 3. Estimation of a Network with Evolutionary Computation; 4. Evaluation of Network Estimation; 5. Estimation and Forecasting with Artificial Data; 6. Times Series: Examples from Industry and Finance; 7. Inflation and Deflation: Hong Kong and Japan; 8. Classification: Credit Card Default and Bank Failures; 9. Dimensionality Reduction and Implied Volatility Forecasting

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