Improving autocorrelation regression for the Hurst parameter estimation of long-range dependent time series based on golden section search

Ming Li, Peidong Zhang and Jianxing Leng

Physica A: Statistical Mechanics and its Applications, 2016, vol. 445, issue C, 189-199

Abstract: This article presents an improved autocorrelation correlation function (ACF) regression method of estimating the Hurst parameter of a time series with long-range dependence (LRD) by using golden section search (GSS). We shall show that the present method is substantially efficient than the conventional ACF regression method of H estimation. Our research uses fractional Gaussian noise as a data case but the method introduced is applicable to time series with LRD in general.

Keywords: Hurst parameter estimation; Autocorrelation regression; Golden section search; Fractional Gaussian noise with long-range dependence (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:445:y:2016:i:c:p:189-199

DOI: 10.1016/j.physa.2015.10.071

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