Abstract
In this paper, we propose a new decision support system for dealing stocks which utilizes information regarding the predictions obtained by NNs concerning the occurrence of the “Golden Cross (GC)” and “Dead Cross (DC)”, those (also obtained by NNs) concerning the rate of change of the future stock price several weeks ahead, and that (also obtained by NNs) concerning the relative position of the stock price versus “GC” and “DC”. Computer simulation results concerning the dealings of the Nikkei-225 for the last 16 years confirm the effectiveness of our approach.
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Baba, N., Liu, K., Han, L.C., Mitsuda, T., Ro, K., Ninn, K. (2011). An Effective Utilization of Many Neural Networks for Improving the Traditional Technical Analysis in the Stock Market. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23863-5_37
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DOI: https://doi.org/10.1007/978-3-642-23863-5_37
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