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Convolution Copula Econometrics

Convolution Copula Econometrics by Umberto Cherubini
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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 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. 
Springer International Publishing; December 2016
99 pages; ISBN 9783319480152
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Title: Convolution Copula Econometrics
Author: Umberto Cherubini; Fabio Gobbi; Sabrina Mulinacci
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