Financial Risk Management with Bayesian Estimation of GARCH Models

Theory and Applications

  • DavidĀ Ardia

Part of the Lecture Notes in Economics and Mathematical System book series (LNE, volume 612)

About this book


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.


Bayesian Financial Risk Management GARCH MCMC Risk Management decision theory regression statistics value at risk value-at-risk

Authors and affiliations

  • DavidĀ Ardia
    • 1
  1. 1.University of Fribourg1700Switzerland

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Business and Economics
  • Print ISBN 978-3-540-78656-6
  • Online ISBN 978-3-540-78657-3
  • Series Print ISSN 0075-8442
  • Buy this book on publisher's site
Industry Sectors
Finance, Business & Banking