Complex dynamical behaviors of daily data series in stock exchange

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)246-255
Journal / PublicationPhysics Letters, Section A: General, Atomic and Solid State Physics
Volume333
Issue number3-4
Publication statusPublished - 6 Dec 2004

Abstract

It is well known that many economic data series show chaotic behaviors. In this Letter, we further investigate the complex dynamical behaviors of the daily data series, including opening quotation, closing quotation, maximum price, minimum price, and total exchange quantum, in Shenzhen stock exchange and Shanghai stock exchange, which are two representative stock exchanges in mainland China. The maximum Lyapunov exponents, correlation dimensions, and frequency spectra are calculated for these time series. Our results indicate that some daily data series of stock exchanges display low-dimensional chaotic behaviors, and some other daily data series do not show any chaotic behavior. Moreover, we introduce a weighted one-rank local-region approach for predicting short-term daily data series of stock exchange. © 2004 Elsevier B.V. All rights reserved.

Research Area(s)

  • Chaotic time series, Correlation dimension, Lyapunov exponent, Spectral analysis, Stock exchange