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Yu , Lean, Wang , Shouyang, Lai , Kin Keung. 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 s, 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.

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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.

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In this monograph, the authors try to apply artificial neural networks ANNs to exchange rates forecasting. 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.

Foreign-Exchange-Rate Forecasting with Artificial Neural Networks

In addition, ANNs have been proved to be a universal fu- tional approximator that can capture any type of complex relationships. Are Foreign Exchange Rates Predictable?

An Improved BP Algorithm with Adaptive Smoothing Momentum Terms for Foreign Exchange Rates Prediction. Predicting Foreign Exchange Market Movement Direction Using a Confidence-Based Neural Network Ensemble Model.

Foreign Exchange Rates Forecasting with Multiple Candidate Models: Developing an Intelligent Forex Rolling Forecasting and Trading Decision Support System II: An Empirical and Comprehensive Assessment.

JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. About this book The foreign exchange market is one of the most complex dynamic markets with the characteristics of high volatility, nonlinearity and irregularity.

Table of contents 10 chapters Are Foreign Exchange Rates Predictable? Basic Learning Principles of Artificial Neural Networks Pages Data Preparation in Neural Network Data Analysis Pages An Improved BP Algorithm with Adaptive Smoothing Momentum Terms for Foreign Exchange Rates Prediction Pages A Nonlinear Combined Model Hybridizing ANN and GLAR for Exchange Rates Forecasting Pages A Hybrid GA-Based SVM Model for Foreign Exchange Market Tendency Exploration Pages Neural Networks Meta-Learning for Foreign Exchange Rate Ensemble Forecasting Pages Predicting Foreign Exchange Market Movement Direction Using a Confidence-Based Neural Network Ensemble Model Pages A Further Discussion Pages An Empirical and Comprehensive Assessment Pages Read this book on SpringerLink Download Preface 1 PDF Services for this Book Download Product Flyer Download High-Resolution Cover.

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