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Random Operators and Stochastic Equations

Editor-in-Chief: Girko, Vyacheslav

Managing Editor: Molchanov, S.

Editorial Board: Accardi, L. / Albeverio, Sergio / Carmona, R. / Casati, G. / Christopeit, N. / Domanski, C. / Drygas, Hilmar / Gupta, A.K. / Ibragimov, I. / Kirsch, Werner / Klein, A. / Kondratyev, Yuri / Kurotschka, V. / Leonenko, N. / Loubaton, Philippe / Orsingher, E. / Pastur, L. / Rodrigues, Waldyr A. / Shiryaev, Albert / Turbin, A.F. / Veretennikov, Alexandre

CiteScore 2018: 0.26

SCImago Journal Rank (SJR) 2018: 0.142
Source Normalized Impact per Paper (SNIP) 2018: 0.375

Mathematical Citation Quotient (MCQ) 2018: 0.11

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Volume 14, Issue 4


Long-range dependence of time series for MSFT data of the prices of shares and returns

Mikhail P. Moklyachuk / Aleksey G. Zrazhevsky

The problem of estimation of the Hurst parameter for self-similar time series is discussed in the paper. Five methods of estimation of the Hurst parameter for prices of MSFT ticker, for returns of MSFT ticker and for simulated FARIMA time series with H = 0.766 are presented. Methods that are inefficient for estimation the Hurst parameter in limit cases (H close to 0.5 and H close to 1) are detected based on the presented methods. The long-range dependence of the mentioned three time series are statistically proved.

Key Words: Hurst parameter,; self-similar time series,; FARIMA time series,; long-range dependence,; MSFT ticker

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Published in Print: 2006-12-01

Citation Information: Random Operators and Stochastic Equations rose, Volume 14, Issue 4, Pages 393–403, ISSN (Online) 1569-397x, ISSN (Print) 0926-6364, DOI: https://doi.org/10.1515/156939706779801714.

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