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Long-range dependence of time series for MSFT data of the prices of shares and returns
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Mikhail P. Moklyachuk
Published/Copyright:
December 1, 2006
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
Published Online: 2006-12-01
Published in Print: 2006-12-01
Copyright 2006, Walter de Gruyter
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Keywords for this article
Hurst parameter,;
self-similar time series,;
FARIMA time series,;
long-range dependence,;
MSFT ticker
Articles in the same Issue
- Comparative stationarity of stochastic exponential and monomial densities
- Stochastic equations with multidimensional drift driven by Levy processes
- On existence of a solution for differential equation with interaction
- Regularity conditions and the maximum likelihood estimation in dynamical systems with small fractional Brownian noise
- On a generalized BSDE involving local time and application to a PDE with nonlinear boundary condition
- Limiting distribution of random motion in a n-dimensional parallelepiped
- Long-range dependence of time series for MSFT data of the prices of shares and returns
