Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/125830 
Year of Publication: 
2015
Series/Report no.: 
CFS Working Paper Series No. 526
Publisher: 
Goethe University Frankfurt, Center for Financial Studies (CFS), Frankfurt a. M.
Abstract: 
Chen and Zadrozny (1998) developed the linear extended Yule-Walker (XYW) method for determining the parameters of a vector autoregressive (VAR) model with available covariances of mixed-frequency observations on the variables of the model. If the parameters are determined uniquely for available population covariances, then, the VAR model is identified. The present paper extends the original XYW method to an extended XYW method for determining all ARMA parameters of a vector autoregressive moving-average (VARMA) model with available covariances of single- or mixed-frequency observations on the variables of the model. The paper proves that under conditions of stationarity, regularity, miniphaseness, controllability, observability, and diagonalizability on the parameters of the model, the parameters are determined uniquely with available population covariances of single- or mixed-frequency observations on the variables of the model, so that the VARMA model is identified with the single- or mixed-frequency covariances.
Subjects: 
block-Vandermonde eigenvectors of block-companion state-transition
matrix of state-space representation
matrix spectral factorization
JEL: 
C32
C80
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
396.95 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.