Convolution copula econometrics
The goal of the book is to gather the main concepts of copula function theory that can be applied to the analysis of time series (so-called convolution-based copulas), and some new ideas, linked to copulas, such as estimation of copula-based Markov processes. Due to the complexity of the subject, the analysis is limited to the univariate setting and the standard first-order Markov processes, that is the AR(1) model. The book consists of 5 chapters. Chapter 1 explores the use of nonparametric analysis that are typical of copula function applications to detect nonlinearities in a time series model. Chapter 2 is mainly focused on the estimation issue. The issue of representation and estimation of Markov processes with copula functions is addressed in Chapter 3. Chapter 4 develops the theory of convolution-based copulas and shows how to estimate and simulate copula of this kind. Finally, Chapter 5 presents an application to the analysis of the dynamics of the short-term interest rate. The book will be useful for the researchers working in econometrics, interest rate, Markov processes and copulas fields.
scientific article; zbMATH DE number 6675714