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Mis-Specification in the Estimation of the Expected Rescaled Adjusted Range Statistic: The Case Versus Peters

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  • Craig Ellis

    (School of Economics and Finance, University of Western Sydney)

Abstract

Rescaled range analysis has in recent times gained in popularity as a means of identifying long memory effects in financial and economic time series data. Conclusions derived from the rescaled adjusted range statistic are conditional however upon the choice of an approptiate benchmark against which observed results can be compared. This paper provides an examination of various models of the expected value of the rescaled adjusted range statistic E(R*/sigma)_n. Two particular models will be cited, those of Anis and Lloyd (1976) and Peters (1994). As will be shown however, there exists significant inconsistencies in empirical results reported by Peters (1994), which when considered reveal Peters' specification of E(R*/sigma)_n should be rejected in favour of that derived by Anis and Lloyd.

Suggested Citation

  • Craig Ellis, 1996. "Mis-Specification in the Estimation of the Expected Rescaled Adjusted Range Statistic: The Case Versus Peters," Working Paper Series 69, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    • Handle: RePEc:uts:wpaper:69
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    References listed on IDEAS

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    1. Peter W.B. Phillips, 1992. "Analysis," Challenge, Taylor & Francis Journals, vol. 35(1), pages 57-59, January.
    2. Graham Newell & Maurice Peat & Max Stevenson, 1996. "Testing for Evidence of Nonlinear Structure in Australian Real Estate Market Returns," Working Paper Series 61, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    3. G. Wenchi Kao & Christopher K. Ma, 1992. "Memories, heteroscedasticity, and price limit in Currency futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 12(6), pages 679-692, December.
    4. Batten, Jonathan & Ellis, Craig, 1996. "Fractal structures and naive trading systems: Evidence from the spot US dollar/Japanese yen," Japan and the World Economy, Elsevier, vol. 8(4), pages 411-421, December.
    5. Cheung, Yin-Wong, 1993. "Long Memory in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 93-101, January.
    6. Brent W. Ambrose & Esther Ancel & Mark D. Griffiths, 1992. "The Fractal Structure of Real Estate Investment Trust Returns: The Search for Evidence of Market Segmentation and Nonlinear Dependency," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 20(1), pages 25-54, March.
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    Cited by:

    1. Howe, John S. & Martin, Deryl W. & WoodJr., Bob G., 1999. "Much ado about nothing: Long-term memory in Pacific Rim equity markets," International Review of Financial Analysis, Elsevier, vol. 8(2), pages 139-151, June.
    2. Craig Ellis, 1998. "Modelling the Expected Value of the Classical Rescaled Adjusted Range for Long-Term Dependent Series," Working Paper Series 79, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    3. Batten, Jonathan A. & Ellis, Craig A. & Fethertson, Thomas A., 2008. "Sample period selection and long-term dependence: New evidence from the Dow Jones index," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1126-1140.

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