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COINTEGRATION RANK TESTING UNDER CONDITIONAL HETEROSKEDASTICITY [PDF]

Econometric Theory, 2009
We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic (martingale difference) innovations. We first demonstrate that
CAVALIERE, GIUSEPPE, A. Rahbek, AMR Taylor   +2 more
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Cointegration tests with conditional heteroskedasticity

Journal of Econometrics, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lee, Tae-Hwy, Tse, Yiuman
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Reprint of: Generalized Autoregressive Conditional Heteroskedasticity

Journal of Econometrics, 2023
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Autoregressive Conditional Heteroskedasticity

2007
All models discussed so far use the conditional expectation to describe the mean development of one or more time series. The optimal forecast, in the sense that the variance of the forecast errors will be minimised, is given by the conditional mean of the underlying model.
Gebhard Kirchgässner, Jürgen Wolters
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Moving average conditional heteroskedastic processes

Economics Letters, 1995
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Yang, Minxian, Bewley, Ronald
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Models of conditional heteroskedasticity

2010
AbstractThis chapter considers modelling conditional heteroskedasticity and begins with the well known autoregressive conditional heteroskedasticity (ARCH) model. Its basic extension to the generalized autoregressive conditional heteroskedasticity (GARCH) model is described, and various extensions of the GARCH model are considered.
Timo Teräsvirta, Dag Tjøstheim, W. J. Granger   +2 more
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Maximum entropy autoregressive conditional heteroskedasticity model

Journal of Econometrics, 2009
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Sung Y. Park, Anil K. Bera
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Non Linear Moving-Average Conditional Heteroskedasticity [PDF]

, 2005
Ever since the appearance of the ARCH model (Engle 1982a), an impressive array of variance specifications belonging to the same class of models has emerged. Despite numerous successful developments, several empirical studies seem to show that their performance is not always appropriate.
Ventosa-Santaulària, Daniel, Mendoza V., Alfonso   +1 more
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Unit root tests with conditional heteroskedasticity

Journal of Econometrics, 1993
Abstract This paper considers the finite-sample accuracy (size) of the Dickey-Fullerunit root tests when the errors are conditionally heteroskedastic. We consider the specific case that the error variance follows a GARCH (1,1) model. The Dickey-Fuller tests tend to overreject in the presence of GARCH errors, but the problem is not very serious except
Kiwhan Kim, Peter Schmidt
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On mixture autoregressive conditional heteroskedasticity

Journal of Statistical Planning and Inference, 2018
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