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800 pp., 1996. Neural Networks in Finance and Investing, Revised 2/E is an updated and expanded edition of the first-ever book on financial applications of neural networks. Robert Trippi and Efraim Turban have assembled here a stellar collection of articles by experts in industry and academia on applications of neural networks in this important arena. This widely-acclaimed classic provides portfolio managers, institutional investors, bankers, and analysts with a comprehensive and fascinating introduction to this important technology and numerous insights into its most effective use. Neural network successes and failures are discussed, as well as the vast unrealized potential of neural networks in numerous specialized areas of financial decision making. Topics include:
Included as a bonus with this new edition is a complimentary version of ThinksPro for Windows, a full-featured neural network software package that can be used for many of the applications described in the book.
Nowhere else will the financial technology professional find such an exciting and relevant in-depth examination of neural networks. Individual chapters discuss how to use neural networks to forecast the stock market, to trade commodities, to assess bond and mortgage risk, to predict bankruptcy, and to implement investment strategies. Taken together, this comprehensive collection provides a fascinating and authoritative introduction to a technology that is revolutionizing the way financial services firms operate.
This unique volume is truly essential reading for anyone wishing to stay abreast of this "cutting edge" technology.
" . . . a landmark book. Packed with difficult-to-find information, this book is the first to comprehensively and clearly address the role of neural networks in financial decision making. It belongs on the bookshelf of every financial analyst and investment manager."
Frank J. Fabozzi, Editor, The Journal of Portfolio Management
"This book clearly describes a new and exciting technology. It makes neural network technology accessible to practitioners through an extraordinary number of real applications. The book contains many examples of neural nets for prediction and risk assessment, as well as a number of promising systems for forecasting or explaining the price movements of stocks and other securities. For practitioners interested in neural networks, this book is a gold mine."
Bruce N. Lehmann, Professor of Economics and Finance, University of California, San Diego
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