Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/32184 
Authors: 
Year of Publication: 
2007
Series/Report no.: 
CoFE Discussion Paper No. 07/13
Publisher: 
University of Konstanz, Center of Finance and Econometrics (CoFE), Konstanz
Abstract: 
We consider parameter estimation for time-dependent locally stationary long-memory processes. The asymptotic distribution of an estimator based on the local infinite autoregressive representation is derived, and asymptotic formulas for the mean squared error of the estimator, and the asymptotically optimal bandwidth are obtained. In spite of long memory, the optimal bandwidth turns out to be of the n-1/5 and inversely proportional to the square of the second derivative of d. In this sense, local estimation of d is comparable to regression smoothing with iid residuals.
Subjects: 
long memory
fractional ARIMA process
local stationarity
bandwidth selection
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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