Convolution Copula Econometrics

• Κύριοι συγγραφείς: Cherubini, Umberto (Συγγραφέας), Gobbi, Fabio (Συγγραφέας), Mulinacci, Sabrina (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Σειρά: SpringerBriefs in Statistics,
• Θέματα: Statistics.; Applied mathematics.; Engineering mathematics.; Probabilities.; Econometrics.; Statistics for Business/Economics/Mathematical Finance/Insurance.; Probability Theory and Stochastic Processes.; Statistical Theory and Methods.; Applications of Mathematics.

 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. 

 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. .