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Record Nr. |
UNINA9910155297503321 |
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Autore |
Cherubini Umberto |
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Titolo |
Convolution copula econometrics [[electronic resource] /] / by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (X, 90 p. 31 illus., 30 illus. in color.) |
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Collana |
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SpringerBriefs in Statistics, , 2191-544X |
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Disciplina |
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Soggetti |
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Statistics |
Probabilities |
Econometrics |
Applied mathematics |
Engineering mathematics |
Statistics for Business, Management, Economics, Finance, Insurance |
Probability Theory and Stochastic Processes |
Statistical Theory and Methods |
Applications of Mathematics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Preface -- The Dynamics of Economic Variables -- Estimation of Copula Models -- Copulas and Estimation of Markov Processes -- Copula-based Markov Processes: Estimation, Mixing Properties and Long-term Behavior -- Convolution-based Processes -- Application to Interest Rates. . |
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Sommario/riassunto |
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This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for |
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econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field. |
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