Economics at your fingertips  

Inference in Non Stationary Asymmetric Garch Models

Christian Francq and Jean-Michel Zakoian

No 2013-11, Working Papers from Center for Research in Economics and Statistics

Abstract: This paper considers the statistical inference of the class of asymmetric power-transformed GARCH(1,1) models in presence of possible explosiveness. We study the explosive behavior of volatility when the strict stationarity condition is not met. This allows us to establish the asymptotic normality of the quasi-maximum likelihood estimator (QMLE) of the parameter, including the power but without the intercept, when strict stationarity does not hold. Two important issues can be tested in this framework: asymmetry and stationarity. The tests exploit the existence of a universal estimator of the asymptotic covariance matrix of the QMLE. By establishing the local asymptotic normality (LAN) property in this nonstationary framework, we can also study optimality issues

Keywords: GARCH models; Inconsistency of estimators; Local power of tests; Non stationarity; Quasi Maximum Likelihood estimation (search for similar items in EconPapers)
Pages: 45
Date: 2013-08
New Economics Papers: this item is included in nep-ets
References: Add references at CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link) Crest working paper version (application/pdf)

Related works:
Working Paper: Inference in non stationary asymmetric garch models (2013) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Working Papers from Center for Research in Economics and Statistics Contact information at EDIRC.
Bibliographic data for series maintained by Secretariat General () and Murielle Jules Maintainer-Email : murielle.jules@ensae.Fr.

Page updated 2024-04-18
Handle: RePEc:crs:wpaper:2013-11