Convolution Copula Econometrics (SpringerBriefs in Statistics)

by Umberto Cherubini, Fabio Gobbi, and Sabrina Mulinacci

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Book cover for Convolution Copula Econometrics

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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.
  • ISBN13 9783319480145
  • Publish Date 16 December 2016
  • Publish Status Active
  • Publish Country CH
  • Imprint Springer International Publishing AG
  • Edition 1st ed. 2016
  • Format Paperback
  • Pages 90
  • Language English