GENERALIZED APPROACH TO HURST EXPONENT ESTIMATING BY TIME SERIES
Journal Title: Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska - Year 2018, Vol 8, Issue 1
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.
Authors and Affiliations
Lyudmyla Kirichenko, Tamara Radivilova, Vitalii Bulakh
Keywords
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- EP ID EP261987
- DOI 10.5604/01.3001.0010.8639
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