Show simple item record

Full bayesian inference for GARCH and EGARCH models

dc.contributor.authorVrontos, Ioannis D.en
dc.contributor.authorDellaportas, Petrosen
dc.contributor.authorPolitis, Dimitris Nicolasen
dc.creatorVrontos, Ioannis D.en
dc.creatorDellaportas, Petrosen
dc.creatorPolitis, Dimitris Nicolasen
dc.date.accessioned2019-12-02T10:38:48Z
dc.date.available2019-12-02T10:38:48Z
dc.date.issued2000
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/57761
dc.description.abstractA full Bayesian analysis of GARCH and EGARCH models is proposed consisting of parameter estimation, model selection, and volatility prediction. The Bayesian paradigm is implemented via Markov-chain Monte Carlo methodologies. We provide implementation details and illustrations using the General Index of the Athens stock exchange. © 2000 Taylor & Francis Group, LLC.en
dc.sourceJournal of Business and Economic Statisticsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-0034403866&doi=10.1080%2f07350015.2000.10524861&partnerID=40&md5=497f3ff40a3ee4f73af55b1be81a58e4
dc.subjectModel averagingen
dc.subjectMarkov-chain Monte Carloen
dc.subjectReversible jumpen
dc.subjectVolatility predictionen
dc.titleFull bayesian inference for GARCH and EGARCH modelsen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1080/07350015.2000.10524861
dc.description.volume18
dc.description.issue2
dc.description.startingpage187
dc.description.endingpage198
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :56</p>en
dc.source.abbreviationJ.Bus.Econ.Stat.en
dc.contributor.orcidVrontos, Ioannis D. [0000-0002-3283-6668]
dc.gnosis.orcid0000-0002-3283-6668


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record