Abstract
In this paper, we propose a new decision support system for dealing stocks which utilizes 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 TOPIX for the last 15 years confirm the effectiveness of our approach.
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References
Rumelhart, D.E., et al.: Parallel Distributed Processing. MIT Press, Cambridge (1986)
Haykin, S.: Neural Networks. Prentice-Hall, Englewood Cliffs (1998)
Baba, N., Kozaki, M.: An intelligent forecasting system of stock price using neural network. In: Proceedings of IJCNN 1992, pp. 371–377 (1992)
Refenes, A.-P.N., et al.: Neural Networks in Financial Engineering: A Study in Methodology. IEEE Trans. NNs, 1222–1267 (1997)
Baba, N., Nomura, T.: 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.) KES 2005. LNCS, vol. 3681, pp. 8–14. Springer, Heidelberg (2005)
Baba, N., Nin, K.: Prediction of Golden Cross and Dead Cross by Neural Networks and Its Utilization. In: Apolloni, B., Howlett, R.J., Jain, L. (eds.) KES 2007, Part II. LNCS, vol. 4693, pp. 642–648. Springer, Heidelberg (2007)
Baba, N., Nin, K.: Prediction of Golden Cross and Dead Cross by Artificial Neural Networks Could Contribute a Lot for Constructing an Intelligent Decision Support System for Dealing Stocks. In: Proc. of ICCAS 2008, pp. 2547–2550 (2008)
Zurada, J.M., et al.: Sensitivity analysis for minimization of joint data dimension for feed forward neural network. In: Proceedings of the IEEE International Symposium on Circuits and Systems, pp. 447–450 (1994)
Harvey, A.C.: Time Series Models. Prentice Hall / Harvester Wheatsheaf (1993)
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Baba, N., Nin, K. (2009). Effective Utilization of Neural Networks for Constructing an Intelligent Decision Support System for Dealing Stocks. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_94
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DOI: https://doi.org/10.1007/978-3-642-04592-9_94
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