Posted by **Rare-1** at July 14, 2015

English | Springer (2008) | ISBN-10: 3540786562 | 206 pages | ُPDF | 7.40 MB

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.

Posted by **DZ123** at Nov. 19, 2010

Publisher: Springer | ISBN: 3540786562 | edition 2008 | PDF | 206 pages | 5,1 mb

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.

Posted by **step778** at Jan. 23, 2016

2008 | pages: 204 | ISBN: 3540786562 | PDF | 7,4 mb

Posted by **step778** at June 11, 2014

2008 | pages: 203 | ISBN: 3540786562 | PDF | 7,4 mb

Posted by **interes** at Feb. 22, 2015

English | 2014 | ISBN: 3658082275 | 69 pages | PDF | 1,5 MB

Posted by **libr** at Dec. 11, 2015

English | May 24, 2011 | ISBN: 0470745843 | 478 pages | PDF | 4,4 MB

Posted by **interes** at Nov. 30, 2013

1 edition | English | May 24, 2011 | ISBN: 0470745843 | 478 pages | PDF | 4,4 MB

The aim of this book is twofold. The first goal is to summarize elementary and advanced topics on modern option pricing: from the basic models of the Black & Scholes theory to the more sophisticated approach based on Lévy processes and other jump processes.

Posted by **fdts** at Dec. 4, 2016

by S.D. Gerking

English | 2013 | ISBN: 9020706284 | 100 pages | PDF | 3.06 MB

Posted by **Underaglassmoon** at Aug. 1, 2016

Springer | Statistics | August 28, 2016 | ISBN-10: 3319327887 | 327 pages | pdf | 3.14 mb

Authors: Phadia, Eswar G.

Provides valuable resource for nonparametric Bayesian analysis of big data

Includes a section on machine learning

Shows practical examples

Posted by **ChrisRedfield** at Dec. 2, 2015

Published: 2013-07-25 | ISBN: 3642392792, 3642429319 | PDF | 207 pages | 2.21 MB