Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations

Bauer D (2008)
Econometric Theory 24(04): 1063-1092.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
This paper deals with the estimation of linear dynamic models of the autoregressive moving average type for the conditional mean for stationary time series with conditionally heteroskedastic innovation process. Estimation is performed using a particular class of subspace methods that are known to have computational advantages as compared to estimation based on criterion minimization. These advantages are especially strong for high-dimensional time series. Conditions to ensure consistency and asymptotic normality of the subspace estimators are derived in this paper. Moreover asymptotic equivalence to quasi maximum likelihood estimators based on the Gaussian likelihood in terms of the asymptotic distribution is proved under mild assumptions on the innovations. Furthermore order estimation techniques are proposed and analyzed.
Erscheinungsjahr
2008
Zeitschriftentitel
Econometric Theory
Band
24
Ausgabe
04
Seite(n)
1063-1092
ISSN
0266-4666
Page URI
https://pub.uni-bielefeld.de/record/2670767

Zitieren

Bauer D. Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations. Econometric Theory. 2008;24(04):1063-1092.
Bauer, D. (2008). Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations. Econometric Theory, 24(04), 1063-1092. doi:10.1017/s0266466608080419
Bauer, D. (2008). Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations. Econometric Theory 24, 1063-1092.
Bauer, D., 2008. Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations. Econometric Theory, 24(04), p 1063-1092.
D. Bauer, “Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations”, Econometric Theory, vol. 24, 2008, pp. 1063-1092.
Bauer, D.: Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations. Econometric Theory. 24, 1063-1092 (2008).
Bauer, Dietmar. “Using subspace methods for estimating arma models for multivariate time series with conditionally heteroskedastic innovations”. Econometric Theory 24.04 (2008): 1063-1092.

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