Convolution Copula Econometrics

By Fabio Gobbi, Sabrina Mulinacci, Umberto Cherubini

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.

• Format: Paperback
• Language: English
• ISBN: 3319480146
• ISBN13: 9783319480145
• Release Date: December 2016
• Publisher: Springer
• Length: 90 Pages
• Weight: 0.34 lbs.
• Dimensions: 0.2" x 6.1" x 9.2"