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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. 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.
    2. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    3. Opong, Kwaku K. & Mulholland, Gwyneth & Fox, Alan F. & Farahmand, Kambiz, 1999. "The behaviour of some UK equity indices: An application of Hurst and BDS tests1," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 267-282, September.
    4. 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.
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    Cited by:

    1. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," CERGE-EI Working Papers wp235, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    2. Gianluca Mattarocci, 2009. "Market Characteristics and Chaos Dynamics in Stock Markets: an International Comparison," Palgrave Macmillan Studies in Banking and Financial Institutions, in: Alessandro Carretta & Franco Fiordelisi & Gianluca Mattarocci (ed.), New Drivers of Performance in a Changing Financial World, chapter 6, pages 89-106, Palgrave Macmillan.
    3. Reidar Hagtvedt, 2009. "Stock return dynamics and the CAPM anomalies," Applied Economics Letters, Taylor & Francis Journals, vol. 16(16), pages 1593-1596.
    4. 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.
    5. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.
    6. A. C. -L. Chian & E. L. Rempel & C. Rogers, 2007. "Crisis-induced intermittency in non-linear economic cycles," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 211-218.
    7. Evzen Kocenda & Lubos Briatka, 2005. "Optimal Range for the iid Test Based on Integration Across the Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 265-296.

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