Dewey Class |
330.015195 |
Title |
Convolution Copula Econometrics ([EBook]) / by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci. |
Author |
Cherubini, Umberto |
Added Personal Name |
Gobbi, Fabio author. |
Mulinacci, Sabrina author. |
Other name(s) |
SpringerLink (Online service) |
Publication |
Cham : : Springer International Publishing : : Imprint: Springer, , 2016. |
Physical Details |
X, 90 p. 31 illus., 30 illus. in color. : online resource. |
Series |
SpringerBriefs in Statistics 2191-544X |
ISBN |
9783319480152 |
Summary Note |
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.: |
Contents note |
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. . |
System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users) |
Internet Site |
http://dx.doi.org/10.1007/978-3-319-48015-2 |
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