Self-organized criticality and stock market dynamics: an empirical study

M. Bartolozzi, D.B. Leinweber and A.W. Thomas

Physica A: Statistical Mechanics and its Applications, 2005, vol. 350, issue 2, 451-465

Abstract: The stock market is a complex self-interacting system, characterized by intermittent behaviour. Periods of high activity alternate with periods of relative calm. In the present work we investigate empirically the possibility that the market is in a self-organized critical state (SOC). A wavelet transform method is used in order to separate high activity periods, related to the avalanches found in sandpile models, from quiescent. A statistical analysis of the filtered data shows a power law behaviour in the avalanche size, duration and laminar times. The memory process, implied by the power law distribution of the laminar times, is not consistent with classical conservative models for self-organized criticality. We argue that a “near-SOC” state or a time dependence in the driver, which may be chaotic, can explain this behaviour.

Keywords: Complex systems; Econophysics; Self-organized criticality; Wavelets (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:350:y:2005:i:2:p:451-465

DOI: 10.1016/j.physa.2004.11.061

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