Abstract
It is shown that ensemble classifiers composed of neural networks trained using particle swarm optimisation can uncover a substantial degree of predictability in stock price movements. As in a previous work by the authors use is made here of a training metric, the Matthews correlation coefficient, that has been shown to better handle numerically unbalanced data sets. The work provides a solid basis for the future construction of a trading model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Grinold, R.C., Kahn, R.N.: Active Portfolio Management. McGraw-Hill, NY (1999)
Litterman, B.: Modern Investment Management. Wiley, NJ (2003)
Khoury, P., Gorse, D.: Identification of Factors Characterising Volatility and Firm-Specific Risk Using Ensemble Classifiers. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part IV. LNCS, vol. 7666, pp. 450–457. Springer, Heidelberg (2012)
Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: IEEE International Conference Symposium on Neural Networks, pp. 1942–1948. IEEE Press, New York (1995)
Poli, R.: An Analysis of Publications on Particle Swarm Optimisation Application. Technical report, Department of Computer Science, University of Essex (2007)
Banks, A., Vincent, J., Anyakoha, C.: An Review of Particle Swarm Optimization. Part II: Hybridisation, Combinatorial, Multicriteria and Constrained Optimization, and Indicative Applications. Natural Computing 7, 109–124 (2008)
Dunis, C., Laws, J., Naïm, P.: Applied Quantitative Methods for Trading and Investment. Wiley, NJ (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Khoury, P., Gorse, D. (2013). Investigation of the Predictability of Steel Manufacturer Stock Price Movements Using Particle Swarm Optimisation. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42042-9_83
Download citation
DOI: https://doi.org/10.1007/978-3-642-42042-9_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42041-2
Online ISBN: 978-3-642-42042-9
eBook Packages: Computer ScienceComputer Science (R0)