Convolution Copula Econometrics. 1st ed. 2016

種類:

電子ブック

責任表示:

by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2016

著者名:

• Cherubini, Umberto.
• Gobbi, Fabio.
• Mulinacci, Sabrina.
• SpringerLink (Online service)

シリーズ名:

SpringerBriefs in Statistics ;

ISBN:

9783319480152 [3319480154]    

注記:

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. .
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.

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