Univariate Conditional Distributions of an Open-Loop TAR Stochastic Process
Clusters of large values are observed in sample paths of certain open-loop threshold autoregressive (TAR) stochastic processes. In order to characterize the stochastic mechanism that generates this empirical stylized fact, three types of marginal conditional distributions of the underlying stochasti...
- Autores:
-
Nieto, Fabio
Moreno, Edna C.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/66516
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/66516
http://bdigital.unal.edu.co/67544/
- Palabra clave:
- 51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
Conditional heteroscedasticity
Nonlinear stochastic process
Open-loop TAR model
Stationary nonlinear stochastic process
Heterocedasticidad condicional
Modelo TAR sin retroalimentación
Proceso estocástico no lineal estacionario.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Clusters of large values are observed in sample paths of certain open-loop threshold autoregressive (TAR) stochastic processes. In order to characterize the stochastic mechanism that generates this empirical stylized fact, three types of marginal conditional distributions of the underlying stochastic process are analyzed in this paper. One allows us to find the conditional variance function that explains the aforementioned stylized fact. As a by-product, we are able to derive a sufficient condition to have asymptotic weak stationarity in an open-loop TAR stochastic process. |
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