Revisiting the relations between Hurst exponent and fractional differencing parameter for long memory
Yan Lin and
Physica A: Statistical Mechanics and its Applications, 2021, vol. 566, issue C
This study aims to verify the efficiency of the estimating methods of long memory process based on the linear relationship between the Hurst exponent (H) and the fractional differencing parameter (d), which are the two approaches used to identify the long memory process. By using the Monte Carlo simulation and empirical examinations, the results show that there is a distinct linear relationship between the Hurst exponent and the fractional differencing parameter. This linear relationship may provide an efficient estimation of the range of Hurst exponent and fractional differencing parameter with each other when the stable index of the stable distribution is close to 2. However, according to the findings, the detailed form of linear equation is impacted by the fat tailed distribution, which becomes more volatile as the stable index of stable distribution is less than 2. Therefore, researchers should be cautious when using the linear relation to estimate H and d them by each other when the distribution has fat tail.
Keywords: Hurst exponent; Fractional differencing parameter; R/S_Com; FELW; Stock market (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:566:y:2021:i:c:s0378437120309018
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().