Designing Short Term Trading Systems with Artificial Neural Networks

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 out-of-sample, and the superiority of the resulting ANN enhanced system is demonstrated.

Authors and Affiliations

1. Technology and Sustainable Development Bond University Gold Coast, Queensland, 4229, Australia

   Bruce Vanstone (Faculty of Business), Gavin Finnie & Tobias Hahn

Editors and Affiliations

1. Harvard School of Engineering and Applied Sciences, Harvard University, 60 Oxford Street, Cambridge, MA, 02138, USA

   Sio-Iong Ao

2. School of Engineering, Dept. of Process and Systems Engineering, Cranfield University, Cranfield, Beds, MK43 0AL, UK

   Len Gelman

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