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...
| Príomhchruthaitheoirí: | , |
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| Formáid: | Working paper |
| Teanga: | English |
| Foilsithe / Cruthaithe: |
Department of Economics (University of Oxford)
2007
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| _version_ | 1826297083371454464 |
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| author | Meitz, M Saikkonen, P |
| author_facet | Meitz, M Saikkonen, P |
| author_sort | Meitz, M |
| collection | OXFORD |
| description | 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 β–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, and only require mild moment conditions. |
| first_indexed | 2024-03-07T04:26:11Z |
| format | Working paper |
| id | oxford-uuid:ccb530a7-fbd6-4b4e-8f15-7048f8a8b9ff |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:26:11Z |
| publishDate | 2007 |
| publisher | Department of Economics (University of Oxford) |
| record_format | dspace |
| spelling | oxford-uuid:ccb530a7-fbd6-4b4e-8f15-7048f8a8b9ff2022-03-27T07:23:45ZStability of nonlinear AR-GARCH models.Working paperhttp://purl.org/coar/resource_type/c_8042uuid:ccb530a7-fbd6-4b4e-8f15-7048f8a8b9ffEnglishOxford University Research Archive - ValetDepartment of Economics (University of Oxford)2007Meitz, MSaikkonen, PThis 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 β–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, and only require mild moment conditions. |
| spellingShingle | Meitz, M Saikkonen, P Stability of nonlinear AR-GARCH models. |
| title | Stability of nonlinear AR-GARCH models. |
| title_full | Stability of nonlinear AR-GARCH models. |
| title_fullStr | Stability of nonlinear AR-GARCH models. |
| title_full_unstemmed | Stability of nonlinear AR-GARCH models. |
| title_short | Stability of nonlinear AR-GARCH models. |
| title_sort | stability of nonlinear ar garch models |
| work_keys_str_mv | AT meitzm stabilityofnonlinearargarchmodels AT saikkonenp stabilityofnonlinearargarchmodels |