Wavelet estimation for locally self-similar processes

LU Zhi-ping; TAO Qin-ying

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Sep. 2012

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Article Navigation > Journal of East China Normal University (Natural Sciences) > 2012 > (5): 76-84

LU Zhi-ping, TAO Qin-ying. Wavelet estimation for locally self-similar processes[J]. Journal of East China Normal University (Natural Sciences), 2012, (5): 76-84.

Citation:

LU Zhi-ping, TAO Qin-ying. Wavelet estimation for locally self-similar processes[J]. Journal of East China Normal University (Natural Sciences), 2012, (5): 76-84.

LU Zhi-ping, TAO Qin-ying. Wavelet estimation for locally self-similar processes[J]. Journal of East China Normal University (Natural Sciences), 2012, (5): 76-84.

Citation:

LU Zhi-ping, TAO Qin-ying. Wavelet estimation for locally self-similar processes[J]. Journal of East China Normal University (Natural Sciences), 2012, (5): 76-84.

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Wavelet estimation for locally self-similar processes

LU Zhi-ping¹,
TAO Qin-ying²

1.
Research Center of International Finance and Risk Management, East China Normal University, Shanghai 200241, China;
2.
Department of Mathematics, East China Normal University, Shanghai 200241, China

Received Date: 2011-12-01
Rev Recd Date: 2012-03-01
Publish Date: 2012-09-25

Abstract

Abstract

A new estimation method was proposed based on the maximal overlap discrete wavelet transform, which provided a good alternative for the estimation of the time-varying self-similarity parameters. It also included a simulation-based study using Monte Carlo method, which increases the accuracy of the estimation. Finally, an application was made on the vertical ocean shear measurements.
- locally self-similar process,
- long memory,
- Monte Carlo simulation,
- OLS regression,
- wavelet transform

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References(1)

References

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