GARCH models without positivity constraints: Exponential or log GARCH?
By Christian Francq, Olivier Wintenberger, Jean-Michel Zakoian. 2012
76 citations recorded by the source corpus.
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on multiplicative volatility dynamics without positivity constraints. We compare the main probabilistic properties (strict stationarity, existence of moments, tails) of the EGARCH model, which are already known, with those of an asymmetric version of the log-GARCH. The quasi-maximum likelihood estimation of the log-GARCH parameters is shown to be strongly consistent and asymptotically normal. Similar estimation results are only available for the EGARCH (1,1) model, and under much stronger assumptions. The comparison is pursued via simulation experiments and estimation on real data.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/cff56b7d54fb0c92d8e251ad61114a3debaeb227
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In Economics and Econometrics
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Citations in the corpus
- Poisson QMLE of Count Time Series Models (2016, background): “XtC1/ <1 and the additional assumption sup 2‚ jˇj < 1, Lemma 7.1 in Francq et al. (2013) shows that lim sup t!”