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Beschreibung
This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.
This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.
Inhaltsverzeichnis
Bayesian Statistics and MCMC Methods.- Bayesian Estimation of the GARCH(1, 1) Model with Normal Innovations.- Bayesian Estimation of the Linear Regression Model with Normal-GJR(1, 1) Errors.- Bayesian Estimation of the Linear Regression Model with Student-t-GJR(1, 1) Errors.- Value at Risk and Decision Theory.- Bayesian Estimation of the Markov-Switching GJR(1, 1) Model with Student-t Innovations.- Conclusion.
Details
Erscheinungsjahr: | 2008 |
---|---|
Fachbereich: | Allgemeines |
Genre: | Wirtschaft |
Rubrik: | Recht & Wirtschaft |
Medium: | Taschenbuch |
Reihe: | Lecture Notes in Economics and Mathematical Systems |
Inhalt: |
xiv
206 S. 27 s/w Illustr. 206 p. 27 illus. |
ISBN-13: | 9783540786566 |
ISBN-10: | 3540786562 |
Sprache: | Englisch |
Herstellernummer: | 12242313 |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Ardia, David |
Hersteller: |
Springer-Verlag GmbH
Springer Berlin Heidelberg Lecture Notes in Economics and Mathematical Systems |
Maße: | 235 x 155 x 13 mm |
Von/Mit: | David Ardia |
Erscheinungsdatum: | 29.05.2008 |
Gewicht: | 0,341 kg |
Inhaltsverzeichnis
Bayesian Statistics and MCMC Methods.- Bayesian Estimation of the GARCH(1, 1) Model with Normal Innovations.- Bayesian Estimation of the Linear Regression Model with Normal-GJR(1, 1) Errors.- Bayesian Estimation of the Linear Regression Model with Student-t-GJR(1, 1) Errors.- Value at Risk and Decision Theory.- Bayesian Estimation of the Markov-Switching GJR(1, 1) Model with Student-t Innovations.- Conclusion.
Details
Erscheinungsjahr: | 2008 |
---|---|
Fachbereich: | Allgemeines |
Genre: | Wirtschaft |
Rubrik: | Recht & Wirtschaft |
Medium: | Taschenbuch |
Reihe: | Lecture Notes in Economics and Mathematical Systems |
Inhalt: |
xiv
206 S. 27 s/w Illustr. 206 p. 27 illus. |
ISBN-13: | 9783540786566 |
ISBN-10: | 3540786562 |
Sprache: | Englisch |
Herstellernummer: | 12242313 |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Ardia, David |
Hersteller: |
Springer-Verlag GmbH
Springer Berlin Heidelberg Lecture Notes in Economics and Mathematical Systems |
Maße: | 235 x 155 x 13 mm |
Von/Mit: | David Ardia |
Erscheinungsdatum: | 29.05.2008 |
Gewicht: | 0,341 kg |
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