Polynomial Cointegration Between Stationary Processes with Long Memory

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Jan 2007 Italy English Publisher:Elsevier BVJournal:SSRN Electronic Journal (eissn: 1556-5068,

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Authors: Avarucci, M.; MARINUCCI, DOMENICO;

doi: 10.2139/ssrn.967397 , 10.1111/j.1467-9892.2007.00540.x , 10.1111/j.0143-9782.2007.00540.x

handle: 2108/34584

Polynomial Cointegration Between Stationary Processes with Long Memory

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Abstract

Abstract. In this article we consider polynomial cointegrating relationships between stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zero.

Country

Italy

Related Organizations

University of Rome Tor Vergata
Italy

Keywords

diagram formula, hermite polynomial, Hermite polynomials, Time series, auto-correlation, regression, etc. in statistics (GARCH), Applications of hypergeometric functions, long memory, nonlinear cointegration, Settore MAT/06 - PROBABILITA' E STATISTICA MATEMATICA, Inference from stochastic processes and spectral analysis, spectral regression, nonlinear cointegration; long memory; hermite polynomials; spectral regression; diagram formula

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