Asymptotics for parametric GARCH-in-Mean models

Christian Conrad and Enno Mammen

Journal of Econometrics, 2016, vol. 194, issue 2, 319-329

Abstract: In this paper we develop an asymptotic theory for the Quasi-Maximum Likelihood Estimator (QMLE) of the parametric GARCH-in-Mean model. The asymptotics is based on a study of the volatility as a process of the model parameters. The proof makes use of stochastic recurrence equations for this random function and uses exponential inequalities to localize the problem. Our results show why the asymptotics for this specification is quite complex although it is a rather standard parametric model. Nevertheless, our theory does not yet treat all standard specifications of the mean function.

Keywords: GARCH-in-Mean; Stochastic recurrence equations; Risk–return relationship (search for similar items in EconPapers)
JEL-codes: C13 C22 C51 G12 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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Working Paper: Asymptotics for parametric GARCH-in-Mean Models (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:194:y:2016:i:2:p:319-329

DOI: 10.1016/j.jeconom.2016.05.010

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