Designing short term trading systems with artificial neural networks
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Electronic versions
DOI
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.
Original language | English |
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Title of host publication | Advances in Electrical Engineering and Computational Science |
Pages | 401-409 |
Number of pages | 9 |
Volume | 39 LNEE |
DOIs | |
Publication status | Published - 2009 |
Externally published | Yes |
Publication series
Name | Lecture Notes in Electrical Engineering |
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