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Published by VDM Verlag Dr. Müller, 2010
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Published by VDM Verlag Dr. Müller, 2010
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Published by VDM Verlag Dr. Mïż½ller 2010-11-03, 2010
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Published by VDM Verlag Dr. Müller, 2010
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Published by VDM Verlag Dr. Müller, 2010
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Taschenbuch. Condition: Neu. Higher-dimensional copula models and their application | Bayesian inference for D-vine pair-copula constructions based on different bivariate families | Jiabao Ma | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2010 | VDM Verlag Dr. Müller | EAN 9783639307061 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.
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Published by VDM Verlag Dr. Müller, 2010
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Published by VDM Verlag Dr. Müller, 2010
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Published by VDM Verlag Dr. Müller, 2010
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Published by VDM Verlag Dr. Müller, 2010
ISBN 10: 3639307062 ISBN 13: 9783639307061
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ma JiabaoJiabao Ma, Dipl.-Math. Oec. Univ.: Studied Mathematical Finance and Economics at Technische Universitaet Muenchen (TUM) in Germany. Investmentcontroller at NORD/LB Asset Management, Hannover, Germany.Modelling multivari.
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Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3639307062 ISBN 13: 9783639307061
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Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
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Published by VDM Verlag Dr. Müller, 2010
ISBN 10: 3639307062 ISBN 13: 9783639307061
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Modelling multivariate dependence structures has proven to be an important aspect in the field of finance. The reality of financial markets shows clear evidence that asset returns exhibit non-normal dependence. Since copula functions have been applied to the solution of these non-normal distributed problems, they find wide-ranging application in the fields of risk management, derivative pricing, hedging and optimal portfolio decisions. Pair-copula construction allows modelling of the dependence structure between different higher-dimensional time series. The author shows a flexible way to estimate and calibrate such higher-dimensional copula models and provides the application of U.S. industrial returns. In his simulation study he shows the sensitivity with respect to the copula parameter and different families using newly developed R-packages.