Bayesian analysis of extreme operational losses

Chyng-Lan Liang

Journal of Operational Risk

Abstract: ABSTRACT Bayesian techniques offer an alternative to parameter estimation methods, such as maximum likelihood estimation, for extreme value models. These techniques treat the parameters to be estimated as random variables, instead of some fixed, possibly unknown, constants. We investigate, with simulated examples, how Bayesian analysis can be used to estimate the parameters of extreme value models, for the case where we have no prior knowledge at all and the case where we have prior knowledge in the form of expert opinion. In addition, Bayesian analysis provides a framework for the incorporation of information from external data into a loss model based on internal data; this is again illustrated using simulation.

References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.risk.net/journal-of-operational-risk/2 ... e-operational-losses (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rsk:journ3:2160849

Access Statistics for this article

More articles in Journal of Operational Risk from Journal of Operational Risk
Bibliographic data for series maintained by Thomas Paine ().