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Fourier-type estimation of the power GARCH model with stable-Paretian innovations

dc.contributor.authorFrancq, Christian
dc.contributor.authorMeintanis, Simos G.
dc.contributor.researchID21262977 - Meintanis, Simos George
dc.date.accessioned2017-05-15T08:22:38Z
dc.date.available2017-05-15T08:22:38Z
dc.date.issued2016
dc.description.abstractWe consider estimation for general power GARCH models under stable-Paretian innovations. Exploiting the simple structure of the conditional characteristic function of the observations driven by these models we propose minimum distance estimation based on the empirical characteristic function of corresponding residuals. Consistency of the estimators is proved, and the asymptotic distribution of the estimator is studied. Efficiency issues are explored and finite-sample results are presented as well as applications of the proposed procedures to real data from the financial markets. A multivariate extension is also considered
dc.identifier.citationFrancq, C. & Meintanis, S.G. 2016. Fourier-type estimation of the power GARCH model with stable-Paretian innovations. Metrika, 79(4):389-424. [https://doi.org/10.1007/s00184-015-0560-x]
dc.identifier.issn0026-1335
dc.identifier.issn1435-926X (Online)
dc.identifier.urihttp://hdl.handle.net/10394/23269
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs00184-015-0560-x
dc.identifier.urihttps://doi.org/10.1007/s00184-015-0560-x
dc.language.isoen
dc.publisherSpringer
dc.subjectGARCH model
dc.subjectMinimum distance estimation
dc.subjectHeavy-tailed distribution
dc.subjectEmpirical characteristic function
dc.titleFourier-type estimation of the power GARCH model with stable-Paretian innovations
dc.typeArticle

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