1.

Record Nr.

UNINA9910155297503321

Autore

Cherubini Umberto

Titolo

Convolution Copula Econometrics / / by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (X, 90 p. 31 illus., 30 illus. in color.)

Collana

SpringerBriefs in Statistics, , 2191-5458

Disciplina

332.015195

Soggetti

Statistics

Probabilities

Econometrics

Mathematics

Statistics in Business, Management, Economics, Finance, Insurance

Probability Theory

Statistical Theory and Methods

Applications of Mathematics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

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. .

Sommario/riassunto

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.