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On The Invertibility Of Multivariate Linear Processes

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  • Saïd Nsiri
  • Roch Roy

Abstract

. It is shown that a multivariate linear stationary process whose coefficients are absolutely summable is invertible if and only if its spectral density is regular everywhere. This general characterization of invertibility is applied later to the case of a linear process having an autoregressive moving‐average (ARMA) representation. Under the usual assumptions, it is deduced that a process Y described by an ARMA(φ, TH) model is invertible if and only if the polynomial detTH(z) has no roots on the unit circle. Given an invertible process Y which has an ARMA representation, it is finally shown that the process YT, where YT, =εi=0lSiYt‐i, is invertible if and only if the matrix S(z) =εi=0lSizi is of full rank for all z of modulus 1. It follows, in particular, that any subprocess of an invertible ARMA process is also invertible.

Suggested Citation

  • Saïd Nsiri & Roch Roy, 1993. "On The Invertibility Of Multivariate Linear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(3), pages 305-316, May.
    • Handle: RePEc:bla:jtsera:v:14:y:1993:i:3:p:305-316
    DOI: 10.1111/j.1467-9892.1993.tb00147.x
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    Cited by:

    1. Wouter J. Den Haan & Andrew T. Levin, 1995. "Inferences from parametric and non-parametric covariance matrix estimation procedures," International Finance Discussion Papers 504, Board of Governors of the Federal Reserve System (U.S.).

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