| |
|
| Artikel-Nr.: 5667A-9783319480145 Herst.-Nr.: 9783319480145 EAN/GTIN: 9783319480145 |
| |
|
| | |
| 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. Weitere Informationen: | | Author: | Umberto Cherubini; Fabio Gobbi; Sabrina Mulinacci | Verlag: | Springer International Publishing | Sprache: | eng |
|
| | |
| | | |
| Weitere Suchbegriffe: 62M05, 60G99, copula functions, convolution-based process, time series analysis, stochastic processes, long memory time series, econometrics, interest rates, autoregressive process, Markov process |
| | |
| |