Neural networks in finance gaining predictive edge in the market
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. Mc...
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Format: | eBook |
Language: | English |
Published: |
Burlington, MA
Elsevier Academic Press
2005
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Series: | Academic Press advanced finance series
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Online Access: | |
Collection: | O'Reilly - Collection details see MPG.ReNa |
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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Physical Description: | xv, 243 pages illustrations |
ISBN: | 9781417577460 9780124859678 1417577460 1592781829 9780080479651 0080479650 9781592781829 |