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Creating Short-Term Stockmarket Trading Strategies Using Artificial Neural Networks: A Case Study, Bruce J. Vanstone, Tobias Hahn
Creating Short-Term Stockmarket Trading Strategies Using Artificial Neural Networks: A Case Study, Bruce J. Vanstone, Tobias Hahn
Tobias Hahn
Developing short-term stockmarket trading systems is a complex process, as there is a great deal of random noise present in the time series data of individual securities. The primary difficulty in training neural networks to identify return expectations is to find variables to help identify the signal present in the data. In this paper, the authors follow the previously published Vanstone and Finnie methodology. They develop a successful neural network, and demonstrate its effectiveness as the core element of a financially viable trading system.
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Tobias Hahn
There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and …