Arbeitspapier
Stability of nonlinear AR-GARCH models
This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Conditions under which the model is stable in the sense that its Markov chain representation is geometrically ergodic are provided. This implies the existence of an initial distribution such that the process is strictly stationary and beta-mixing. Conditions under which the stationary distribution has finite moments are also given. The results cover several nonlinear specifications recently proposed for both the conditional mean and conditional variance.
- Sprache
-
Englisch
- Erschienen in
-
Series: SSE/EFI Working Paper Series in Economics and Finance ; No. 632
- Klassifikation
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
ARCH-Modell
Markovscher Prozess
Heteroskedastizität
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Meitz, Mika
Saikkonen, Pentti
- Ereignis
-
Veröffentlichung
- (wer)
-
Stockholm School of Economics, The Economic Research Institute (EFI)
- (wo)
-
Stockholm
- (wann)
-
2006
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Meitz, Mika
- Saikkonen, Pentti
- Stockholm School of Economics, The Economic Research Institute (EFI)
Entstanden
- 2006
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