Univariate Conditional Distributions of an Open-Loop TAR Stochastic Process

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...

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Veröffentlicht in:Revista Colombiana de Estadística 2016-07, Vol.39 (2), p.149-165
Hauptverfasser: Nieto, Fabio, Moreno, Edna C.
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Sprache:eng
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Conditional heteroscedasticity
Datasets
Nonlinear stochastic process
Nonlinear systems
Open-loop TAR model
Stationary nonlinear stochastic process
Stochastic models
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description 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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subjects Conditional heteroscedasticity
Datasets
Nonlinear stochastic process
Nonlinear systems
Open-loop TAR model
Stationary nonlinear stochastic process
Stochastic models
title Univariate Conditional Distributions of an Open-Loop TAR Stochastic Process
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