Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering

The Nonlinear Dynamics Characteristics of Stock Market and Its Variation

Authors
Jun Meng, Tianyu Zhu, Xiao Chen, Xiang Yin
Corresponding Author
Jun Meng
Available Online March 2013.
DOI
https://doi.org/10.2991/iccsee.2013.116How to use a DOI?
Keywords
stock market, Dow Jones indexes, correlation dimension, the maximum Lyapunov exponent, phase space reconstructiontt
Abstract
The stock market is a kind of complex system with all kinds of interactions. It also shows a nonlinear characteristic. In this paper, we analysed the time series from Dow Jones indexes itself and the time series from its fluctuation difference and extracted its correlation dimension and Lyapunov exponent, which shows a chaotic dynamic characteristic in it. Moreover, we also analysed the variation of chaotic characteristic indexes in long term, and found that the correlation dimension has a quasi-periodical variation and some rapid drops in some specific years. The variation of the correlation dimension can be used to reflect some internal changes in stock market.
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Proceedings
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
978-90-78677-61-1
DOI
https://doi.org/10.2991/iccsee.2013.116How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jun Meng
AU  - Tianyu Zhu
AU  - Xiao Chen
AU  - Xiang Yin
PY  - 2013/03
DA  - 2013/03
TI  - The Nonlinear Dynamics Characteristics of Stock Market and Its Variation
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iccsee.2013.116
DO  - https://doi.org/10.2991/iccsee.2013.116
ID  - Meng2013/03
ER  -