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Neural networks in finance [electronic resource] : gaining predictive edge in the market / Paul D. McNelis.

By: McNelis, Paul D.
Material type: TextTextSeries: Academic Press advanced finance series: Publisher: Burlington, MA : Elsevier Academic Press, c2005Description: 1 online resource (xv, 243 p.) : ill.ISBN: 1417577460 (electronic bk.); 9781417577460 (electronic bk.); 1592781829 (electronic bk. : Adobe Reader); 9781592781829 (electronic bk. : Adobe Reader); 9780124859678; 0124859674; 0080479650 (electronic bk.); 9780080479651.Subject(s): Finance -- Decision making -- Data processing | Neural networks (Computer science) | BUSINESS & ECONOMICS -- Finance | Finances -- Prise de d�ecision -- Informatique | R�eseaux neuronaux (Informatique) | Financieel management | Neurale netwerken | Prognoses (vorm) | Wiskundige modellenGenre/Form: Electronic books. | Electronic books.Additional physical formats: Print version:: Neural networks in finance.DDC classification: 332/.0285/632 Online resources: EBSCOhost
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.
Summary: 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.
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Includes bibliographical references p. ([221]-231).

Description based on print version record.

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.

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.

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Other editions of this work

Neural networks in finance by McNelis, Paul D. ©2005
Neural networks in finance by McNelis, Paul D. ©2005
Neural networks in finance by McNelis, Paul D. ©2005
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