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ON M-Estimation Under Long-Range Dependence in Volatility

Beran, Jan

Journal of time series analysis, 2007-01, Vol.28 (1), p.138-153 [Periódico revisado por pares]

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Título:
ON M-Estimation Under Long-Range Dependence in Volatility
Autor: Beran, Jan
Assuntos: central limit theorem ; Estimating techniques ; location estimation ; Long-range dependence ; M-estimator ; Normal distribution ; Studies ; volatility
É parte de: Journal of time series analysis, 2007-01, Vol.28 (1), p.138-153
Notas: istex:00E29A81066EB1B08DA884B9293E6ED4BBF86FE1
ark:/67375/WNG-KRWK6Z9H-M
ArticleID:JTSA506
Descrição: . 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.
Editor: Oxford, UK: Blackwell Publishing Ltd
Idioma: Inglês

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