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dc.contributor.authorPackham, Natalie-
dc.contributor.authorPapenbrock, Jochen-
dc.contributor.authorSchwendner, Peter-
dc.contributor.authorWoebbeking, Fabian-
dc.date.accessioned2019-08-08T08:41:36Z-
dc.date.available2019-08-08T08:41:36Z-
dc.date.issued2015-12-11-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/17866-
dc.description.abstractWe develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalised innovations. These generalised innovations may for example follow a Student t, a Generalised hyperbolic, an alpha-stable or a Generalised Pareto (GPD) distribution. Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods.de_CH
dc.format.extent25de_CH
dc.language.isoende_CH
dc.publisherSocial Science Research Networkde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc332: Finanzwirtschaftde_CH
dc.titleTail-risk protection trading strategiesde_CH
dc.typeWorking Paper – Gutachten – Studiede_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitut für Wealth & Asset Management (IWA)de_CH
dc.identifier.doi10.2139/ssrn.2702275de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.author.additionalNode_CH
Appears in Collections:Publikationen School of Management and Law

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