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GARCH models without positivity constraints: Exponential or log GARCH?

  • ENSAE
  • Université de Lille

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)34-46
Number of pages13
JournalJournal of Econometrics
Volume177
Issue number1
DOIs
Publication statusPublished - 1 Jan 2013
Externally publishedYes

Keywords

  • EGARCH
  • Log-GARCH
  • Quasi-maximum likelihood
  • Strict stationarity
  • Tail index

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