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Classical and modified rescaled range analysis: Sampling properties under heavy tails

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Abstract

Mostly used estimators of Hurst exponent for detection of long-range dependence are biased by presence of short-range dependence in the underlying time series. We present confidence intervals estimates for rescaled range and modified rescaled range. We show that the difference in expected values and confidence intervals enables us to use both methods together to clearly distinguish between the two types of processes. Moreover, both methods are robust against the presence of heavy tails in the underlying process.

Suggested Citation

  • Ladislav Kristoufek, 2009. "Classical and modified rescaled range analysis: Sampling properties under heavy tails," Working Papers IES 2009/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2009.
  • Handle: RePEc:fau:wpaper:wp2009_26
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    Keywords

    rescaled range; modified rescaled range; Hurst exponent; long-range dependence; confidence intervals;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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