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Foreign-Exchange-Rate Forecasting with Artificial Neural Networks

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Cover of 'Foreign-Exchange-Rate Forecasting with Artificial Neural Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Are Foreign Exchange Rates Predictable? — A Literature Review from Artificial Neural Networks Perspective
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    Chapter 2 Basic Learning Principles of Artificial Neural Networks
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    Chapter 3 Data Preparation in Neural Network Data Analysis
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    Chapter 4 Forecasting Foreign Exchange Rates Using an Adaptive Back-Propagation Algorithm with Optimal Learning Rates and Momentum Factors
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    Chapter 5 An Online BP Learning Algorithm with Adaptive Forgetting Factors for Foreign Exchange Rates Forecasting
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    Chapter 6 An Improved BP Algorithm with Adaptive Smoothing Momentum Terms for Foreign Exchange Rates Prediction
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    Chapter 7 Hybridizing BPNN and Exponential Smoothing for Foreign Exchange Rate Prediction
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    Chapter 8 A Nonlinear Combined Model Hybridizing ANN and GLAR for Exchange Rates Forecasting
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    Chapter 9 A Hybrid GA-Based SVM Model for Foreign Exchange Market Tendency Exploration
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    Chapter 10 Forecasting Foreign Exchange Rates with a Multistage Neural Network Ensemble Model
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    Chapter 11 Neural Networks Meta-Learning for Foreign Exchange Rate Ensemble Forecasting
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    Chapter 12 Predicting Foreign Exchange Market Movement Direction Using a Confidence-Based Neural Network Ensemble Model
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    Chapter 13 Foreign Exchange Rates Forecasting with Multiple Candidate Models: Selecting or Combining? A Further Discussion
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    Chapter 14 Developing an Intelligent Forex Rolling Forecasting and Trading Decision Support System I: Conceptual Framework, Modeling Techniques and System Implementations
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    Chapter 15 Developing an Intelligent Forex Rolling Forecasting and Trading Decision Support System II: An Empirical and Comprehensive Assessment
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