Neural Networks in Finance: Gaining Predictive Edge in the Market (Academic Press Advanced Finance Series)

This book 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. 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. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website. Read more... This book 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.

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.

* Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance
* Includes numerous examples and applications
* Numerical illustrations use MATLAB code and the book is accompanied by a website Content: Front Matter , Page iii Copyright , Page iv Preface , Pages xi-xv 1 - Introduction , Pages 1-10 2 - What Are Neural Networks? , Pages 13-58 3 - Estimation of a Network with Evolutionary Computation , Pages 59-84 4 - Evaluation of Network Estimation , Pages 85-111 5 - Estimating and Forecasting with Artificial Data , Pages 115-143 6 - Times Series: Examples from Industry and Finance , Pages 145-166 7 - Inflation and Deflation: Hong Kong and Japan , Pages 167-197 8 - Classification: Credit Card Default and Bank Failures , Pages 199-210 9 - Dimensionality Reduction and Implied Volatility Forecasting , Pages 211-220 Bibliography , Pages 221-231 Index , Pages 233-243 This book shows how neural networks may be put to work for more accurate forecasting, classification, and dimensionality reduction for better decision making in financial markets-particularly in the volatile emerging markets of Asia and Latin America, but also in domestic industrialized-country asset markets and business environments.