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Fractal analysis revisited: The case of the US industrial sector stocks

Author

Listed:
  • Taro Ikeda

    () (Graduate School of Economics, Kobe University)

Abstract

In contrast to earlier studies of long memories, this paper indicates that most of the US industrial sector stocks have the long memories when we consider the structural changes for the Hurst exponents

Suggested Citation

  • Taro Ikeda, 2017. "Fractal analysis revisited: The case of the US industrial sector stocks," Economics Bulletin, AccessEcon, vol. 37(2), pages 666-674.
  • Handle: RePEc:ebl:ecbull:eb-16-00854
    as

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    File URL: http://www.accessecon.com/Pubs/EB/2017/Volume37/EB-17-V37-I2-P61.pdf
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    References listed on IDEAS

    as
    1. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    2. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
    3. Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
    4. Artwell Chimanga & Chipo Mlambo, 2014. "The Fractal Nature Of The Johannesburg Stock Exchange," The African Finance Journal, Africagrowth Institute, vol. 16(1), pages 39-56.
    5. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Fractal geometry; Hurst exponent; long memory;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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