Financial Risk Management with Bayesian Estimation of GARCH Models Theory and Applications /

For his excellent monograph, David Ardia won the Chorafas prize 2008 at the University of Fribourg Switzerland. This book presents methodologies for the Bayesian estimation of GARCH models and their application to financial risk management. The study of these models from a Bayesian viewpoint is rela...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ardia, David (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Lecture Notes in Economics and Mathematical Systems, 612
Temas:
Econometrics.
Macroeconomics.
Statistics .
Social sciences > Mathematics.
Macroeconomics and Monetary Economics.
Statistics in Business, Management, Economics, Finance, Insurance.
Mathematics in Business, Economics and Finance.
Acceso en línea:Texto Completo
Descripción
Sumario:For his excellent monograph, David Ardia won the Chorafas prize 2008 at the University of Fribourg Switzerland. This book presents methodologies for the Bayesian estimation of GARCH models and their application to financial risk management. The study of these models from a Bayesian viewpoint is relatively recent and can be considered very promising due to the advantages of the Bayesian approach, in particular the possibility of obtaining small-sample results and integrating these results in a formal decision model. The first two chapters introduce the work and give an overview of the Bayesian paradigm for inference. The next three chapters describe the estimation of the GARCH model with Normal innovations and the linear regression models with conditionally Normal and Student-t-GJR errors. The sixth chapter shows how agents facing different risk perspectives can select their optimal Value at Risk Bayesian point estimate and documents that the differences between individuals can be substantial in terms of regulatory capital. The last chapter proposes the estimation of a Markov-switching GJR model.
Descripción Física:XIV, 206 p. 27 illus. online resource.
ISBN:9783540786573
ISSN:2196-9957 ;

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