Foreign-Exchange-Rate Forecasting with Artificial Neural Networks

Yu Lean Wang Shouyang Lai Kin Keung

ISBN 10: 1441944044 / ISBN 13: 9781441944047

Verlag: Springer, 2010

Beschreibung

Print on Demand pp. 342 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Bestandsnummer des Verkäufers 5818982

Bibliografische Details

• Titel: Foreign-Exchange-Rate Forecasting with Artificial Neural Networks
• Verlag: Springer
• Erscheinungsjahr: 2010
• Sprache: Englisch
• ISBN-10: 1441944044
• ISBN-13: 9781441944047
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

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.

Críticas

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)