Foreign-Exchange-Rate Forecasting with Artificial Neural Networks

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Springer Science & Business Media, Feb 26, 2010 - Business & Economics - 316 pages
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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Contents

Forecasting Foreign Exchange Rates with Artificial
3
Basic Learning Principles of Artificial Neural Networks 27 2 1 Introduction
27
Individual Neural Network Models with Optimal
63
An Online BP Learning Algorithm with Adaptive Forgetting
86
An Improved BP Algorithm with Adaptive Smoothing
101
Hybridizing ANN with Other Forecasting
119
A Nonlinear Combined Model Hybridizing ANN and GLAR
132
Rates Forecasting 175 10 Forecasting Foreign Exchange Rates with a Multistage Neural
177
Neural Networks MetaLearning for Foreign Exchange Rate
203
Predicting Foreign Exchange Market Movement Direction
217
Foreign Exchange Rates Forecasting with Multiple Candidate
232
Developing an Intelligent Foreign Exchange
246
Developing an Intelligent Forex Rolling Forecasting
275
References
291
Subject Index
311
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