ON M-Estimation Under Long-Range Dependence in Volatility
We consider M-estimation of a location parameter for processes with zero autocorrelations but long-range dependence in volatility. The observed process is the product of i.i.d. Gaussian observations and a long-memory Gaussian process. For nonlinear estimators, the rate of convergence depends on the type of the ψ-function. For skew-symmetric ψ-functions, a central limit theorem with -rate of convergence holds, under suitable regularity assumptions. This is not true in general for M-estimators where the ψ-function is not skewsymmetric. Copyright 2007 The Author Journal compilation 2007 Blackwell Publishing Ltd.
Year of publication: |
2007
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Authors: | Beran, Jan |
Published in: |
Journal of Time Series Analysis. - Wiley Blackwell, ISSN 0143-9782. - Vol. 28.2007, 1, p. 138-153
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Publisher: |
Wiley Blackwell |
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