Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/44948 
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dc.contributor.authorBade, Alexanderen
dc.contributor.authorFrahm, Gabrielen
dc.contributor.authorJaekel, Uween
dc.date.accessioned2011-04-14T12:29:18Z-
dc.date.available2011-04-14T12:29:18Z-
dc.date.issued2008-
dc.identifier.urihttp://hdl.handle.net/10419/44948-
dc.description.abstractWe develop a general approach to portfolio optimization taking account of estimation risk and stylized facts of empirical finance. This is done within a Bayesian framework. The approximation of the posterior distribution of the unknown model parameters is based on a parallel tempering algorithm. The portfolio optimization is done using the first two moments of the predictive discrete asset return distribution. For illustration purposes we apply our method to empirical stock market data where daily asset logreturns are assumed to follow an orthogonal MGARCH process with t-distributed perturbations. Our results are compared with other portfolios suggested by popular optimization strategies.en
dc.language.isoengen
dc.publisher|aUniversity of Cologne, Seminar of Economic and Social Statistics |cCologneen
dc.relation.ispartofseries|aDiscussion Papers in Statistics and Econometrics |x1/08en
dc.subject.ddc330en
dc.subject.keywordBayesian portfolio optimizationen
dc.subject.keywordGordin's conditionen
dc.subject.keywordMarkov chain Monte Carloen
dc.subject.keywordStylized factsen
dc.titleA general approach to Bayesian portfolio optimization-
dc.typeWorking Paperen
dc.identifier.ppn656253371en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:ucdpse:108en

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