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Neural networks for financial forecasting
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Neural networks for financial forecasting

by Edward Gately, Perry J. Kaufman

This guide examines the application of neural networks in financial price forecasting. It details the construction and training of automated trading systems, providing technical foundations for modelling and predicting market values through data analysis.

Accession 10473 ISBN 9780471112129 Publisher John Wiley & Sons
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TAGS
Curated Derived
Computer Science Crime Culture Economics Finance Money Prediction Social Sciences Technology
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on_shelf
True
position_updated_at
2026-06-01 16:44
orientation
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Hard Back
dimensions
none captured
spine_text
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LOCATION HISTORY
M:N3:32 3 Current vertical
2 weeks ago
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Last synced 2026-05-21 00:50 (2 weeks, 6 days ago)

Identity

name→ title
Neural networks for financial forecasting
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10473
vernon_slug
neural-networks-for-financial-forecasting-edward-gately-series-editor-perry-j-kaufman

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isbn_issn→ isbn (when valid)
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Descriptive

production_date
[1996]
object_type
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object_status
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brief_description
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. -- publisher's blurb.

Subjects & people

authors→ author (initial fill only)
Edward Gately, Perry J. Kaufman
tags→ tags
Social sciences, Civilisation, Economics, Computer systems, Electronic data processing, Computers, Neural networks (Computer science), Soft computing, Investments, Finance, Money market, Day trading (Securities), Electronic trading of securities, Securities -- Data processing, Futures, Financial futures, Forecasting, Business forecasting, Economic forecasting, Program trading (Securities)
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