Neural networks in the capital markets

Abstract

PART ONE: NEURAL NETWORKS: Introduction Design Considerations Methods for Optimal Network Design Data Modelling Considerations Testing Strategies and Metrics PART TWO: EQUITY APPLICATIONS: Modelling Stock Returns in the Framework of APT: A Comparative Study with Regression Models Testing the Efficient Markets Hypothesis with Gradient Descent Algorithms Neural Networks as an Alternative Market Model PART THREE: FOREIGN EXCHANGE APPLICATIONS: The Foreign Exchange Markets Nonlinear Modelling of the US$/DM Exchange Rate Managing Exchange Rate Trading Strategies Financial Market Applications of Learning from Hints Machine Learning for Foreign Exchange Trading Indicator Selection PART FOUR: BOND APPLICATIONS: Criteria for Performance in Gilt Futures Pricing Bond Rating with Neural Networks PART FIVE: MACRO-ECONOMIC FORECASTING APPLICATIONS: Bankruptcy Prediction: a Comparison of Discriminant Analysis with Neural Networks Predicting Corporate Mergers Using Backpropagation Networks Self-Organizing Neural Networks: the Financial State of Spanish Companies.