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Convolution Copula econometrics

Cherubini, Umberto.

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Convolution Copula econometrics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Convolution Copula econometrics/ by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci.
作者:	Cherubini, Umberto.
其他作者:	Gobbi, Fabio.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	x, 90 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Copulas (Mathematical statistics) -
電子資源:	http://dx.doi.org/10.1007/978-3-319-48015-2
ISBN:	9783319480152

Convolution Copula econometrics
Cherubini, Umberto.

Convolution Copula econometrics[electronic resource] /by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci. - Cham :Springer International Publishing :2016. - x, 90 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

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.

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 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.

ISBN: 9783319480152

Standard No.: 10.1007/978-3-319-48015-2doiSubjects--Topical Terms:

1086625
Copulas (Mathematical statistics)

LC Class. No.: QA273.6

Dewey Class. No.: 519.535

Convolution Copula econometrics
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520 $a 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 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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