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Foreign-Exchange-Rate Forecasting with Artificial Neural Networks: 107 (International Series in Operations Research & Management Science, 107) - Hardcover
Synopsis
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.
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Review
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)
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- PublisherSpringer
- Publication date2007
- ISBN 10 0387717196
- ISBN 13 9780387717197
- BindingHardcover
- LanguageEnglish
- Number of pages339
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges. 344 pp. Englisch. Seller Inventory # 9780387717197
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Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
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ISBN 10: 0387717196
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9780387717197
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