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Volatility Estimators in Econometric Analysis of Risk Transfer on Capital Markets

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dc.contributor.author Fałdziński, Marcin
dc.contributor.author Osińska, Magdalena
dc.date.accessioned 2017-04-18T12:00:40Z
dc.date.available 2017-04-18T12:00:40Z
dc.date.issued 2016-12-28
dc.identifier.citation Dynamic Econometric Models, No. 1, Vol. 16, pp. 21-35
dc.identifier.issn 2450-7067
dc.identifier.other doi:10.12775/DEM.2016.002
dc.identifier.uri http://repozytorium.umk.pl/handle/item/4159
dc.description.abstract The purpose of the research is to compare the performance of different volatility measures while used in testing for causality in risk between several emerging and mature capital markets. The following volatility estimators are considered: Parkinson, Garman-Klass, Rogers-Satchell, Garman-Klass-Yang-Zhang and Yang-Zhang and the AR-GARCH(1,1)-t model. Additionally, the extreme value theory is also applied. Several emerging capital markets are checked for being the source of the risk for both emerging and developed markets. The group of emerging markets includes the most intensively  growing economies in the world. The final results are such as the number of relationships between the markets is considerably lower when the methods taken from the extreme value theory are used.
dc.language.iso eng
dc.rights Attribution-NoDerivs 3.0 Poland
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by-nd/3.0/pl/
dc.subject causality in risk
dc.subject extreme value theory
dc.subject growing emerging economies
dc.subject risk transfer
dc.subject volatility
dc.title Volatility Estimators in Econometric Analysis of Risk Transfer on Capital Markets
dc.type info:eu-repo/semantics/article


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