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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
By Paul D. McNelis
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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