Convolution Copula Econometrics

von Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci

90 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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. 

• Reihe: SpringerBriefs in Statistics
• Themen: Mathematik und Naturwissenschaften Mathematik Wahrscheinlichkeitsrechnung und Statistik
• ISBN: 9783319480145
• Sprache: Englisch
• Erscheinungsdatum: 16.12.2016
• Größe: 23.5 x 15.5 cm
• Verlag: Springer International Publishing