Abstract
The use of soft computing techniques such as neural networks and fuzzy engineering in the financial market has recently become one of the most exciting and promising application areas. In this paper, we propose a new decision support system (DSS) for dealing stocks which improves the traditional technical analysis by using neural networks. In the proposed system, neural networks are utilized in order to predict the “Golden Cross”(“Dead Cross”) several weeks before it occurs. Computer simulation results concerning the dealings of the Nikkei-225 confirm the effectiveness of the proposed DSS.
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Baba, N., Nomura, T. (2005). An Intelligent Utilization of Neural Networks for Improving the Traditional Technical Analysis in the Stock Markets. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_2
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DOI: https://doi.org/10.1007/11552413_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28894-7
Online ISBN: 978-3-540-31983-2
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