Dynamic Interaction Networks in modelling and predicting the behaviour of multiple interactive stock markets

Widiputra, H
Pears, R
Serguieva, A
Kasabov, N
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
John Wiley & Sons

The behaviour of multiple stock markets can be described within the framework of complex dynamic systems. A representative technique of the framework is the dynamic interaction network (DIN), recently developed in the bioinformatics domain. DINs are capable of modelling dynamic interactions between genes and predicting their future expressions. In this paper, we adopt a DIN approach to extract and model interactions between stock markets. The network is further able to learn online and updates incrementally with the unfolding of the stock market time-series. The approach is applied to a case study involving 10 market indexes in the Asia Pacific region. The results show that the DIN model reveals important and complex dynamic relationships between stock markets, demonstrating the ability of complex dynamic systems approaches to go beyond the scope of traditional statistical methods.

Complex dynamic systems , Interactive stock markets , Dynamic interaction networks , Online learning , Time-series prediction
Journal of Intelligent System in Accounting, Finance and Management, vol.16(1), pp.189 - 205
Publisher's version
Rights statement
Copyright © 2009 John Wiley & Sons. All rights reserved. Authors retain the right to place his/her pre-publication version of the work on a personal website or institutional repository. This article may not exactly replicate the final version published in (please see citation) as it is not a copy of this record. An electronic version of this article can be found online at: (Please see Publisher’s Version)