Mikhail P. Moklyachuk, Aleksey G. Zrazhevsky
Long-range dependence of time series for MSFT data of the prices of shares and returns
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.
Random Operators and Stochastic Equations, Walter de Gruyter
Print ISSN: 0926-6364
Volume: 14, 12/2006
Pages: 393 - 403
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