| 書(shū)目名稱(chēng) | Foreign-Exchange-Rate Forecasting with Artificial Neural Networks | | 編輯 | Lean Yu,Shouyang Wang,Kin Keung Lai | | 視頻video | http://file.papertrans.cn/346/345404/345404.mp4 | | 概述 | The book’s modeling framework is multi-level enabling agent of an intelligent foreign-exchange-rate-forecasting methodology. Adding to the methodology is a decision-support system, which can be delive | | 叢書(shū)名稱(chēng) | International Series in Operations Research & Management Science | | 圖書(shū)封面 |  | | 描述 | 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 appe | | 出版日期 | Book 2007 | | 關(guān)鍵詞 | algorithms; artificial neural networks; decision support system; ensemble learning; forecasting; foreign | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-71720-3 | | isbn_softcover | 978-1-4419-4404-7 | | isbn_ebook | 978-0-387-71720-3Series ISSN 0884-8289 Series E-ISSN 2214-7934 | | issn_series | 0884-8289 | | copyright | Springer-Verlag US 2007 |
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