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Not all estimators are born equal: The empirical properties of some estimators of long memory

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  • Rea, William
  • Oxley, Les
  • Reale, Marco
  • Brown, Jennifer

Abstract

We present the results of a simulation study into the properties of 12 different estimators of the Hurst parameter, H, or the fractional integration parameter, d, in long memory time series which are available in R packages. We compare and contrast their performance on simulated Fractional Gaussian Noises and fractionally integrated series with lengths between 100 and 10,000 data points and H values between 0.55 and 0.90 or d values between 0.05 and 0.40. We apply all 12 estimators to the Campito Mountain data and estimate the accuracy of their estimates using the Beran goodness-of-fit test for long memory time series.

Suggested Citation

  • Rea, William & Oxley, Les & Reale, Marco & Brown, Jennifer, 2013. "Not all estimators are born equal: The empirical properties of some estimators of long memory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 29-42.
    • Handle: RePEc:eee:matcom:v:93:y:2013:i:c:p:29-42
    DOI: 10.1016/j.matcom.2012.08.005
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    Cited by:

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    2. Michael McAleer & Felix Chan & Les Oxley, 2013. "Modeling and Simulation: An Overview," Working Papers in Economics 13/18, University of Canterbury, Department of Economics and Finance.
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    5. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.

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    More about this item

    Keywords

    Strong dependence; Global dependence; Long range dependence; Hurst parameter estimators;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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