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2012-11-06Masterarbeit DOI: 10.18452/14177
Semi-parametric estimation of elliptical distribution in case of high dimensionality
dc.contributor.authorPimenova, Irina
dc.date.accessioned2017-06-18T02:35:14Z
dc.date.available2017-06-18T02:35:14Z
dc.date.created2012-11-12
dc.date.issued2012-11-06
dc.identifier.urihttp://edoc.hu-berlin.de/18452/14829
dc.description.abstractThis paper is devoted to the problem of high dimensionality in finance. We consider a joint multivariate density estimator of elliptical distribution which relies on a non-parametric estimation of a generator function. The factor model is employed in order to obtain a consistent covariance matrix estimator. We provide a simulation study that suggests that the considered estimator significantly outperforms the one based on the sample covariance matrix estimator. We also provide an empirical study using an example of a S&P500 portfolio. The returns of the resulted distribution are fat tailed and have a high peak. The comparison with other distributions illustrates the inappropriateness of normal or Student t distribution to fit the financial returns. Calculations of VaR are provided as an example of possible applications.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectcovariance matrixeng
dc.subjecthigh dimensionalityeng
dc.subjectfactor modelseng
dc.subjectelliptical distributionseng
dc.subject.ddc330 Wirtschaft
dc.titleSemi-parametric estimation of elliptical distribution in case of high dimensionality
dc.typemasterThesis
dc.identifier.urnurn:nbn:de:kobv:11-100205587
dc.identifier.doihttp://dx.doi.org/10.18452/14177
dc.identifier.alephidBV040534612
dc.contributor.refereeHärdle, Wolfgang Karl
dc.contributor.refereeOkhrin, Ostap
local.edoc.pages70
local.edoc.type-nameMasterarbeit
local.edoc.institutionWirtschaftswissenschaftliche Fakultät

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