Neural Networks for Financial Forecasting (Wiley Trader's Exchange) [Hardcover]

Edward Gately (Author)

Book Description

Publication Date: October 6, 1995 | ISBN-10: 0471112127 | ISBN-13: 978-0471112129 | Edition: 1

Succinctly explains how neural networks function, what they can accomplish as well as how to use, construct and apply them for maximum profit. Selecting what is to be predicted and choosing proper inputs, deciding on the best network architecture, training, and algorithms are among the topics discussed. Highlights examples of successful networks. Numerous graphs and spreadsheets are used to illustrate concepts. The appendix features lists of neural network suppliers, useful publications and more.

Editorial Reviews

From the Publisher

Succinctly explains how neural networks function, what they can accomplish as well as how to use, construct and apply them for maximum profit. Selecting what is to be predicted and choosing proper inputs, deciding on the best network architecture, training, and algorithms are among the topics discussed. Highlights examples of successful networks. Numerous graphs and spreadsheets are used to illustrate concepts. The appendix features lists of neural network suppliers, useful publications and more.

From the Inside Flap

Neural Networks for Financial Forecasting Neural networks are interconnecting systems set up to function like the neuron patterns of the human brain, learning by a process of trial and error. When applied to the world of finance, neural networks are automated trading systems, based on mapping inputs and outputs for forecasting probable future values. In Neural Networks for Financial Forecasting-the first book to focus on the role of neural networks specifically in price forecasting-traders are provided with a solid foundation that explains how neural nets work, what they can accomplish, and how to construct, use, and apply them for maximum profit. It is written by an acknowledged authority who is, himself, the developer of several successful networks. Beginning with an examination of the structure of a typical network, the author defines what they can and cannot predict. Then, step-by-step, he explains how to design, build, train, and use exactly the kind of network that best suits your forecasting needs, from deciding what is to be predicted and selecting the appropriate inputs, to designing the network architecture and training algorithms to meet your specific goals. Guidelines help you determine when to stop training, and there are tips on what to try if your network won't train, or memorizes rather than generalizes. Also included are discussions on the amount of data you'll need, as well as the preprocessing of data, so that it is in a form usable to the network. Most importantly, you'll learn how to bring all the elements together. Neural Networks for Financial Forecasting enables you to develop a usable, state-of-the-art network from scratch all the way through completion of training. There are spreadsheets and graphs throughout to illustrate key points, and an appendix of valuable information, including neural network software suppliers and related publications. This is comprehensive, targeted information on some of the most important technology in finance today.

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Product Details

• Hardcover: 169 pages
• Publisher: Wiley; 1 edition (October 6, 1995)
• Language: English
• ISBN-10: 0471112127
• ISBN-13: 978-0471112129
• Product Dimensions: 9.4 x 6.6 x 0.6 inches
• Shipping Weight: 14.4 ounces
• Average Customer Review: 2.4 out of 5 stars  See all reviews (5 customer reviews)
• Amazon Best Sellers Rank: #299,270 in Books (See Top 100 in Books)
  • #42 in Books > Computers & Technology > Computer Science > Artificial Intelligence > Neural Networks

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Customer Reviews

Most Helpful Customer Reviews

30 of 31 people found the following review helpful:

1.0 out of 5 stars poor and misleading, September 27, 1999

By A Customer

This review is from: Neural Networks for Financial Forecasting (Wiley Trader's Exchange) (Hardcover)

About the only positive thing I can say is that he has done a good job at capturing the feel of the trial and error process that is so necessary in developing a neural network model. That said, I could write a book about what's wrong with the book. There is so much poor advice and misinformation in the book, I would scarcely know where to begin. As I read it, I literally cringed at the so-called "information" being passed on to the unaware.

His errors includes poor sampling of test data, no validation data, poor data preparation, highly correlated inputs, small sample size, basing design changes in on insignificant changes in error, etc.

The extensive bibliography may be useful to some, but I would bet my net worth that it is not a list of books he has read. If you have a copy of Azoff's book on forecasting, you will find that Gately essentially cribbed the bulk of his bibliography from Azoff. The few remaining entries were cribbed from the bibliography found in the Neuroshell literature. The book is fairly heavy with hype for the Neuroshell product. (Not that it's a bad product.)

If you're thinking of buying this, I would recommend instead Master's Practical Neural Networks in C++. Doesn't matter if you don't program, it has plenty of good text, and most importantly, sound advice.

16 of 16 people found the following review helpful:

1.0 out of 5 stars Gately's results are very misleading, December 17, 1999

By A Customer

This review is from: Neural Networks for Financial Forecasting (Wiley Trader's Exchange) (Hardcover)

The reviewer that wrote the poor and misleading review described the book perfectly.

In a 4 page passage of the book I found at least 10 errors involving contradictions between text, tables and figures. This becomes very frustrating if you are trying to reproduce the results Gately achieved--a task I have found impossible.

Gately also claims great success however he does not test his neural nets on a validation set of data. This is a fatal error in real trading. It is therefor impossible to determine if he was successful at all.

It is clear that Gately does not have a background in quantitative sciences, as he has little skill in accurately and completely reporting procedures and results.

The idea of the book and the trial and error approach is good but another author should write the second edition.

10 of 10 people found the following review helpful:

1.0 out of 5 stars This book says very little about Neural Networks, May 9, 1998

By 

[e-mail] (PA, USA) - See all my reviews

This review is from: Neural Networks for Financial Forecasting (Wiley Trader's Exchange) (Hardcover)

This book offers a lot and delivers very little. For one thing, it gives no theory of NN, instead it wastes one full chapter on the brain and NN's. The front page offers to show "Top techniques for designing and applying the latest.....", but this is false advertizing!. In short, VERY DISAPPOINTING!.