Neural network time series forecasting of financial markets

Neural Network Time Series Forecasting of Financial Markets E. Michael Azoff The first comprehensive and practical introduction to using neural networks in financial time series forecasting. This practical working guide shows you how to understand, design and profitably use neural network techniques in financial market forecasting. It encompasses: A tutorial introduction to neural networks Data preprocessing Key network design issues Random walk probability theory Fully specified benchmarks (and code for implementing the benchmarks as pre-trained networks) An overview of futures trading Discussion of trading systems and risk management The book focuses on the multilayer perception, one of the most powerful and successful network architectures that is used in the majority of commercial applications, especially financial time series forecasting. The fully specified benchmarks are a unique feature of the book and will be of particular benefit if you are contemplating designing your own neural network using one of the many commercial simulators.