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International Series in Operations Research & Management Science

Foreign-Exchange-Rate Forecasting with Artificial Neural Networks

Authors: Yu, Lean, Wang, Shouyang, Lai, Kin Keung

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  • Focuses on forecasting foreign exchange rates via artificial neural networks (ANNs)
  • The book’s modeling framework is multi-level enabling agent of an intelligent foreign-exchange-rate-forecasting methodology.
  • Includes a decision-support system, which can be delivered by both a client/server model and widely-used web technologies
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About this book

The foreign exchange market is one of the most complex dynamic markets with the characteristics of high volatility, nonlinearity and irregularity. Since the Bretton Woods System collapsed in 1970s, the fluctuations in the foreign exchange market are more volatile than ever. Furthermore, some important factors, such as economic growth, trade development, interest rates and inflation rates, have significant impacts on the exchange rate fluctuation. Meantime, these characteristics also make it extremely difficult to predict foreign exchange rates. Therefore, exchange rates forecasting has become a very important and challenge research issue for both academic and ind- trial communities. In this monograph, the authors try to apply artificial neural networks (ANNs) to exchange rates forecasting. Selection of the ANN approach for - change rates forecasting is because of ANNs’ unique features and powerful pattern recognition capability. Unlike most of the traditional model-based forecasting techniques, ANNs are a class of data-driven, self-adaptive, and nonlinear methods that do not require specific assumptions on the und- lying data generating process. These features are particularly appealing for practical forecasting situations where data are abundant or easily available, even though the theoretical model or the underlying relationship is - known. Furthermore, ANNs have been successfully applied to a wide range of forecasting problems in almost all areas of business, industry and engineering. In addition, ANNs have been proved to be a universal fu- tional approximator that can capture any type of complex relationships.

Reviews

From the reviews:

"This monograph consisting of six parts focuses on forecasting exchange rates via artificial neural networks (ANNs) and it is based on the fruit of a very pleasant scientific cooperation between three genuine academic researchers. …The academic researchers together with the business practitioners interested in the recent developments concerning the forecasting foreign exchange rates with ANNs will find in this book an excellent reference." (Vasile Postolica, Zentralblatt MATH, Vol. 1125 (2), 2008)


Table of contents (15 chapters)

Table of contents (15 chapters)
  • Are Foreign Exchange Rates Predictable? — A Literature Review from Artificial Neural Networks Perspective

    Pages 3-23

  • Basic Learning Principles of Artificial Neural Networks

    Pages 27-37

  • Data Preparation in Neural Network Data Analysis

    Pages 39-62

  • Forecasting Foreign Exchange Rates Using an Adaptive Back-Propagation Algorithm with Optimal Learning Rates and Momentum Factors

    Pages 65-85

  • An Online BP Learning Algorithm with Adaptive Forgetting Factors for Foreign Exchange Rates Forecasting

    Pages 87-100

Buy this book

eBook $129.00
price for USA in USD (gross)
  • ISBN 978-0-387-71720-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-0-387-71719-7
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
Softcover $169.99
price for USA in USD
  • ISBN 978-1-4419-4404-7
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
Authors
Series Title
International Series in Operations Research & Management Science
Series Volume
107
Copyright
2007
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-0-387-71720-3
DOI
10.1007/978-0-387-71720-3
Hardcover ISBN
978-0-387-71719-7
Softcover ISBN
978-1-4419-4404-7
Series ISSN
0884-8289
Edition Number
1
Number of Pages
XXIII, 316
Topics

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