Neural networks in finance : gaining predictive edge in the market /

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Bibliographic Details
Author / Creator:McNelis, Paul D.
Imprint:Burlington, MA : Elsevier Academic Press, ©2005.
Description:1 online resource (xv, 243 pages) : illustrations
Language:English
Series:Academic Press advanced finance series
Academic Press advanced finance series.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11133415
Hidden Bibliographic Details
ISBN:1417577460
9781417577460
1592781829
9781592781829
0080479650
9780080479651
9780124859678
0124859674
Notes:Includes bibliographical references pages (221-231).
Print version record.
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.
Other form:Print version: McNelis, Paul D. Neural networks in finance. Burlington, MA : Elsevier Academic Press, ©2005 0124859674