Convolution Copula econometrics

• 作者： Cherubini, Umberto, author.
• 其他作者：
  • Gobbi, Fabio, author.
  • Mulinacci, Sabrina, author.
  • SpringerLink (Online service)
• 其他題名：
  • SpringerBriefs in statistics.
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： SpringerBriefs in statistics,
• 主題： Copulas (Mathematical statistics) , Econometrics. , Statistics. , Statistics for Business/Economics/Mathematical Finance/Insurance. , Probability Theory and Stochastic Processes. , Econometrics. , Statistical Theory and Methods. , Applications of Mathematics.
• ISBN： 9783319480152 (electronic bk.) 、 9783319480145 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: 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.
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• 摘要註: 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.
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