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Empirical asset return distributions: is chaos the culprit?

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  • Cal Muckley

Abstract

This study employs Rescaled-range analysis; the Correlation Dimension test, and the BDS test, to analyse lengthy daily time series of financial data. Two equity and two commodity indices are examined. The results reject the hypothesis that the series are purely random, independent and identically distributed. Rather, they suggest consistency with the Pareto-Levy family of processes. Motivated by the capacity of certain chaotic models to generate data consistent with these processes, evidence is accumulated consistent with a strange attractor, a long-term memory effect, and a-periodic motion. The evidence is consistent with insights derived from the theory of non-linear dynamics.

Suggested Citation

  • Cal Muckley, 2004. "Empirical asset return distributions: is chaos the culprit?," Applied Economics Letters, Taylor & Francis Journals, vol. 11(2), pages 81-86.
  • Handle: RePEc:taf:apeclt:v:11:y:2004:i:2:p:81-86
    DOI: 10.1080/1350485042000200150
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    References listed on IDEAS

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    1. Adrangi, Bahram & Chatrath, Arjun & Dhanda, Kanwalroop Kathy & Raffiee, Kambiz, 2001. "Chaos in oil prices? Evidence from futures markets," Energy Economics, Elsevier, vol. 23(4), pages 405-425, July.
    2. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
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    Cited by:

    1. Mattarocci, Gianluca, 2006. "Market characteristics and chaos dynamics in stock markets: an international comparison," MPRA Paper 4296, University Library of Munich, Germany, revised Jun 2006.
    2. He, Kaijian & Lu, Xingjing & Zou, Yingchao & Keung Lai, Kin, 2015. "Forecasting metal prices with a curvelet based multiscale methodology," Resources Policy, Elsevier, vol. 45(C), pages 144-150.

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