Business Commons^™

An Empirical Methodology For Developing Stockmarket Trading Systems Using Artificial Neural Networks, Bruce J. Vanstone, Gavin Finnie

Bruce Vanstone

A great deal of work has been published over the past decade on the application of neural networks to stockmarket trading. Individual researchers have developed their own techniques for designing and testing these neural networks, and this presents a difficulty when trying to learn lessons and compare results. This paper aims to present a methodology for designing robust mechanical trading systems using soft computing technologies, such as artificial neural networks. This methodology describes the key steps involved in creating a neural network for use in stockmarket trading, and places particular emphasis on designing these steps to suit the real-world constraints …

Trading In The Australian Stockmarket Using Artificial Neural Networks, Bruce Vanstone

Bruce Vanstone

This thesis focuses on training and testing neural networks for use within stockmarket trading systems. It creates and follows a well defined methodology for developing and benchmarking trading systems which contain neural networks.

Four neural networks and consequently four trading systems are presented within this thesis. The neural networks are trained using all fundamental or all technical variables, and are trained on different segments of the Australian stockmarket, namely all ordinary shares, and the S&P/ASX200 constituents.

Three of the four trading systems containing neural networks significantly outperform the respective buy-and-hold returns for their segments of the market, demonstrating that neural …