A model for level induced conditional heteroskedasticity

Jon Michel and Robert de Jong

Statistics & Probability Letters, 2019, vol. 145, issue C, 293-300

Abstract: A class of conditional heteroskedasticity models is introduced and analyzed. This class of models is motivated by the desire to allow the level of a GARCH process to influence the volatility. We show the existence of a unique strictly stationary solution which is β-mixing. The analysis of this model does not rely upon Markov chain methods.

Keywords: Conditional heteroskedasticity; GARCH; β-mixing; Nonlinear time series (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:145:y:2019:i:c:p:293-300

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DOI: 10.1016/j.spl.2018.10.011

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