Testing for Nonlinearity and Deterministic Chaos in Monthly Japanese Stock Market Data
It has been widely recognised that the randomness of a stock market may actually be an indicator of an underlying strange attractor which has a fractal structure and supports chaotic motion. The application of non-linear methods to such financial data may indicate the presence of nonlinearities and low-dimensional chaos. These methods include rescaled range (R/S) analysis, correlation dimension calculation and estimation of Lyapunov exponents. This study presents a preliminary analysis of these tests when applied to the monthly TOPIX data of the Tokyo Stock Exchange. Although there are a number of limitations for applied non-linear methods such as the presence of noise and limited data size, the results indicate the presence of nonlinearities and the long memory effect in the observed data set. In order to complement these methods, neural networks are used for non-linear modelling and the prediction of the TOPIX data. The results can serve as an additional evidence of a deterministic system by givig accuracy estimates for short-term prediction.
Volume (Year): 1 (1998)
Issue (Month): 1 (May)
|Contact details of provider:|| Postal: |
Phone: +385 1 233-5633
Fax: +385 1 238-3333
Web page: http://www.efzg.hr/
More information through EDIRC
|Order Information:|| Postal: Zagreb International Review of Economics and Business, Faculty of Economics and Business, Trg J. F. Kennedy 6, 10000 Zagreb, Croatia.|
Web: http://www.efzg.hr/default.aspx?id=6045 Email:
When requesting a correction, please mention this item's handle: RePEc:zag:zirebs:v:1:y:1998:i:1:p:61-81. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jurica Šimurina)
If references are entirely missing, you can add them using this form.