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Non-periodic Australian Stock Market Cycles: Evidence from Rescaled Range Analysis

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  • McKenzie, Michael D
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    Abstract

    The standard complement of statistical techniques used to identify predictable market structure is only capable of identifying regular periodic cycles and assumes that the data are independent and identically distributed (i.i.d.). Yet financial returns data are not independent and cycles are most probably not periodic. Rescaled range analysis is a nonparametric technique that can distinguish the average cycle length of irregular cycles. Using Australian stock market data, this paper finds evidence of long memory in the returns generating process and non-periodic cycles of approximately 3, 6, and 12 years in average duration. Copyright 2001 by The Economic Society of Australia.

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    Bibliographic Info

    Article provided by The Economic Society of Australia in its journal The Economic Record.

    Volume (Year): 77 (2001)
    Issue (Month): 239 (December)
    Pages: 393-406

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    Handle: RePEc:bla:ecorec:v:77:y:2001:i:239:p:393-406

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    Cited by:
    1. John Goddard & Enrico Onali, 2014. "Self-affinity in financial asset returns," Papers 1401.7170, arXiv.org.
    2. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    3. Cornelis A. Los & Jeyanthi Karuppiah, 2004. "Wavelet Multiresolution Analysis of High-Frequency Asian FX Rates, Summer 1997," Finance 0409037, EconWPA.
    4. Jun Nagayasu, 2003. "The Efficiency of the Japanese Equity Market," IMF Working Papers 03/142, International Monetary Fund.
    5. Sang-Hoon Kang & Hoa Nguyen, 2007. "Long Memory in the Australian Stock Market," Accounting, Finance, Financial Planning and Insurance Series 2007_18, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
    6. David G. McMillan & Pako Thupayagale, 2009. "The efficiency of African equity markets," Studies in Economics and Finance, Emerald Group Publishing, vol. 26(4), pages 275-292, October.
    7. Enrico Onali & John Goddard, 2014. "Are European equity markets efficient? New evidence from fractal analysis," Papers 1402.1440, arXiv.org.
    8. Kristoufek, Ladislav, 2009. "Procesy s dlouhou pamětí a jejich vývoj ve výnosech indexu PX v letech 1999 – 2009
      [Long-term memory and its evolution in returns of PX between 1999 and 2009]
      ," MPRA Paper 16435, University Library of Munich, Germany.

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