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Convolution Copula Econometrics (Paperback) (Umberto Cherubini & Fabio Gobbi & Sabrina Mulinacci)
About this item
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.
Genre: Business + Money Management, Mathematics
Series Title: Springerbriefs in Statistics
Publisher: Springer Verlag
Author: Umberto Cherubini & Fabio Gobbi & Sabrina Mulinacci
Street Date: December 16, 2016
Item Number (DPCI): 248-33-9438
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