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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association: With Applications to Financial Time-Series - Tapa blanda
Sinopsis
Putting a particular emphasis on nonparametric methods that rely on modern empirical process techniques, the author contributes to the theory of static and time-varying stochastic models for multivariate association based on the concept of copulas. These functions enable a profound understanding of multivariate association, which is pivotal for judging whether a large set of risky assets entails diversification effects or aggravates risk from an entrepreneurial point of view. Since serial dependence is a stylized fact of financial time series, an asymptotic theory for estimating the structure of association in this context is developed under weak assumptions. A new measure of multivariate association, based on a notion of distance to stochastic independence, is introduced. Asymptotic results as well as hypothesis tests are established which are directly applicable to important types of multivariate financial time series. To ensure that risk management properly captures the current structure of association, it is crucial to assess the constancy of the structure. Therefore, nonparametric tests for a constant copula with either a specified or unspecified change point (candidate) are derived. The thesis concludes with a study of characterizations of association between non-continuous random variables.
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Martin Ruppert, born in Worms, Germany, in 1982, holds a 2007 degree in Mathematics with a minor in Business Administration from the Technical University of Darmstadt. In 2011, he completed his doctoral studies at the Graduate School of Risk Management and the Department of Economic and Social Statistics at the University of Cologne. He has written articles on dependence modeling, and has given presentations on this subject at several conferences.
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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Josef Eul Verlag Gmbh, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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Josef Eul Verlag Gmbh Jan 2012, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Putting a particular emphasis on nonparametric methods that rely on modern empirical process techniques, the author contributes to the theory of static and time-varying stochastic models for multivariate association based on the concept of copulas. These functions enable a profound understanding of multivariate association, which is pivotal for judging whether a large set of risky assets entails diversification effects or aggravates risk from an entrepreneurial point of view. Since serial dependence is a stylized fact of financial time series, an asymptotic theory for estimating the structure of association in this context is developed under weak assumptions. A new measure of multivariate association, based on a notion of distance to stochastic independence, is introduced. Asymptotic results as well as hypothesis tests are established which are directly applicable to important types of multivariate financial time series. To ensure that risk management properly captures the current structure of association, it is crucial to assess the constancy of the structure. Therefore, nonparametric tests for a constant copula with either a specified or unspecified change point (candidate) are derived. The thesis concludes with a study of characterizations of association between non-continuous random variables. 176 pp. Englisch. Nº de ref. del artículo: 9783844101201
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association : With Applications to Financial Time-Series
Publicado por
Josef Eul Verlag Gmbh, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Putting a particular emphasis on nonparametric methods that rely on modern empirical process techniques, the author contributes to the theory of static and time-varying stochastic models for multivariate association based on the concept of copulas. These functions enable a profound understanding of multivariate association, which is pivotal for judging whether a large set of risky assets entails diversification effects or aggravates risk from an entrepreneurial point of view. Since serial dependence is a stylized fact of financial time series, an asymptotic theory for estimating the structure of association in this context is developed under weak assumptions. A new measure of multivariate association, based on a notion of distance to stochastic independence, is introduced. Asymptotic results as well as hypothesis tests are established which are directly applicable to important types of multivariate financial time series. To ensure that risk management properly captures the current structure of association, it is crucial to assess the constancy of the structure. Therefore, nonparametric tests for a constant copula with either a specified or unspecified change point (candidate) are derived. The thesis concludes with a study of characterizations of association between non-continuous random variables. Nº de ref. del artículo: 9783844101201
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Contributions to Static and Timevarying Copulabased Modeling of Multivariate Association With Applications to Financial TimeSeries
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Contributions to Static and Timevarying Copulabased Modeling of Multivariate Association With Applications to Financial TimeSeries
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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ISBN 10: 3844101209
ISBN 13: 9783844101201
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorMartin Ruppert, born in Worms, Germany, in 1982, holds a 2007 degree in Mathematics with a minor in Business Administration from the Technical University of Darmstadt. In 2011, he completed his doctoral studies at the . Nº de ref. del artículo: 5470261
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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Josef Eul Verlag GmbH 2012-01, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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Josef Eul Verlag Gmbh, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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Josef Eul Verlag Gmbh, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Contributions to Static and Time-varying Copula-based Modeling of Multivariate Association
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Josef Eul Verlag Gmbh, Josef Eul Verlag Gmbh Jan 2012, 2012
ISBN 10: 3844101209
ISBN 13: 9783844101201
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Taschenbuch. Condición: Neu. Neuware -Putting a particular emphasis on nonparametric methods that rely on modern empirical process techniques, the author contributes to the theory of static and time-varying stochastic models for multivariate association based on the concept of copulas. These functions enable a profound understanding of multivariate association, which is pivotal for judging whether a large set of risky assets entails diversification effects or aggravates risk from an entrepreneurial point of view. Since serial dependence is a stylized fact of financial time series, an asymptotic theory for estimating the structure of association in this context is developed under weak assumptions. A new measure of multivariate association, based on a notion of distance to stochastic independence, is introduced. Asymptotic results as well as hypothesis tests are established which are directly applicable to important types of multivariate financial time series. To ensure that risk management properly captures the current structure of association, it is crucial to assess the constancy of the structure. Therefore, nonparametric tests for a constant copula with either a specified or unspecified change point (candidate) are derived. The thesis concludes with a study of characterizations of association between non-continuous random variables.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch. Nº de ref. del artículo: 9783844101201
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