Discrete Fourier Transforms of Fractional Processes
AbstractDiscrete Fourier transforms (dft's) of fractional processes are studied and an exact representation of the dft is given in terms of the component data. The new representation gives the frequency domain form of the model for a fractional process, and is particularly useful in analyzing the asymptotic behavior of the dft and periodogram in the nonstationary case when the memory parameter d >= 1/2. Various asymptotic approximations are suggested. It is shown that smoothed periodogram spectral estimates remain consistent for frequencies away from the origin in the nonstationary case provided the memory parameter d
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1243.
Length: 59 pages
Date of creation: Dec 1999
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Find related papers by JEL classification:
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- Corbae, D. & Ouliaris, S. & Phillips, P.C.B., 1997.
"Band Spectral Regression with Trending Data,"
97-09, University of Iowa, Department of Economics.
- Peter C.B. Phillips, 1999.
"Unit Root Log Periodogram Regression,"
Cowles Foundation Discussion Papers
1244, Cowles Foundation for Research in Economics, Yale University.
- Peter C.B. Phillips, 1985. "Fractional Matrix Calculus and the Distribution of Multivariate Tests," Cowles Foundation Discussion Papers 767, Cowles Foundation for Research in Economics, Yale University.
- Peter C.B. Phillips, 1988. "Spectral Regression for Cointegrated Time Series," Cowles Foundation Discussion Papers 872, Cowles Foundation for Research in Economics, Yale University.
- Peter C.B. Phillips & Victor Solo, 1989. "Asymptotics for Linear Processes," Cowles Foundation Discussion Papers 932, Cowles Foundation for Research in Economics, Yale University.
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