1 option
Convolution Copula Econometrics / by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci.
Springer Nature - Springer Mathematics and Statistics eBooks 2016 English International Available online
View online- Format:
- Book
- Author/Creator:
- Cherubini, Umberto, Author.
- Gobbi, Fabio, Author.
- Mulinacci, Sabrina, Author.
- Series:
- SpringerBriefs in Statistics, 2191-5458
- Language:
- English
- Subjects (All):
- Statistics.
- Probabilities.
- Econometrics.
- Mathematics.
- Statistics in Business, Management, Economics, Finance, Insurance.
- Probability Theory.
- Statistical Theory and Methods.
- Applications of Mathematics.
- Local Subjects:
- Statistics in Business, Management, Economics, Finance, Insurance.
- Probability Theory.
- Econometrics.
- Statistical Theory and Methods.
- Applications of Mathematics.
- Physical Description:
- 1 online resource (X, 90 p. 31 illus., 30 illus. in color.)
- Edition:
- 1st ed. 2016.
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2016.
- Summary:
- 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:
- 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. .
- Notes:
- Includes bibliographical references at the end of each chapters.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.