GENERALIZED APPROACH TO HURST EXPONENT ESTIMATING BY TIME SERIES

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DOI

Lyudmyla Kirichenko

lyudmyla.kirichenko@nure.ua

Tamara Radivilova

tamara.radivilova@gmail.com

Vitalii Bulakh

bulakhvitalii@gmail.com

Abstract

This paper presents a generalized approach to the fractal analysis of self-similar random processes by short time series. Several stages of the fractal analysis are proposed. Preliminary time series analysis includes the removal of short-term dependence, the identification of true long-term dependence and hypothesis test on the existence of a self-similarity property. Methods of unbiased interval estimation of the Hurst exponent in cases of stationary and non-stationary time series are discussed. Methods of estimate refinement are proposed. This approach is applicable to the study of self-similar time series of different nature.

Keywords:

self-similar stochastic process, time series, Hurst exponent

References

Article Details

Kirichenko, L., Radivilova, T., & Bulakh, V. (2018). GENERALIZED APPROACH TO HURST EXPONENT ESTIMATING BY TIME SERIES. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 8(1), 28–31. https://doi.org/10.5604/01.3001.0010.8639