Convolution Copula Econometrics

di Umberto Cherubini (Autore)

Fabio Gobbi (Autore)

Sabrina Mulinacci (Autore)

Springer International Publishing AG, 2016

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. 

• Autore: Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci
• Editore: Springer International Publishing AG
• Collana: SpringerBriefs in Statistics
• Anno: 2016
• Rilegatura: Paperback / softback
• Pagine: 90 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319480145

Testo in English