File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
  • Find via Find It@HKUL
Supplementary

Article: Nonparametric Bayesian Credibility

TitleNonparametric Bayesian Credibility
Authors
KeywordsNonparametric Bayesian credibility
Risk characteristic of policyholder
Random probability distribution
Credibility premium principle
Dirichlet process
Issue Date2009
PublisherInstitute of Actuaries of Australia. The Journal's web site is located at http://www.actuaries.asn.au/TechnicalResources/ActuaryJournals.aspx
Citation
Australian Actuarial Journal, 2009, v. 15 n. 2, p. 209-230 How to Cite?
AbstractThis paper introduces nonparametric Bayesian credibility without imposing stringent parametric assumptions on claim distributions. We suppose that a claim distribution associated with an unknown risk characteristic of a policyholder is an unknown parameter vector with infinite dimension. In this way, we incorporate the uncertainty of the functional form of the claim distribution associated with the unknown risk characteristic in calculating credibility premiums. Using the results of Ferguson (1973), formulas of the Bayesian credibility premiums are obtained. The formula for the Bayesian credibility pure premium is a linear combination of the overall mean and the sample mean of the claims. This is consistent with the result in the classical credibility theory. We perform a simulation study for the nonparametric Bayesian credibility pure premiums and compare them with the corresponding Bühlmann credibility premiums. Estimation results for the credibility premiums using Danish fire insurance loss data are presented.
Persistent Identifierhttp://hdl.handle.net/10722/125400
ISSN

 

DC FieldValueLanguage
dc.contributor.authorSiu, TKen_HK
dc.contributor.authorYang, Hen_HK
dc.date.accessioned2010-10-31T11:29:15Z-
dc.date.available2010-10-31T11:29:15Z-
dc.date.issued2009en_HK
dc.identifier.citationAustralian Actuarial Journal, 2009, v. 15 n. 2, p. 209-230en_HK
dc.identifier.issn1442-3065-
dc.identifier.urihttp://hdl.handle.net/10722/125400-
dc.description.abstractThis paper introduces nonparametric Bayesian credibility without imposing stringent parametric assumptions on claim distributions. We suppose that a claim distribution associated with an unknown risk characteristic of a policyholder is an unknown parameter vector with infinite dimension. In this way, we incorporate the uncertainty of the functional form of the claim distribution associated with the unknown risk characteristic in calculating credibility premiums. Using the results of Ferguson (1973), formulas of the Bayesian credibility premiums are obtained. The formula for the Bayesian credibility pure premium is a linear combination of the overall mean and the sample mean of the claims. This is consistent with the result in the classical credibility theory. We perform a simulation study for the nonparametric Bayesian credibility pure premiums and compare them with the corresponding Bühlmann credibility premiums. Estimation results for the credibility premiums using Danish fire insurance loss data are presented.-
dc.languageengen_HK
dc.publisherInstitute of Actuaries of Australia. The Journal's web site is located at http://www.actuaries.asn.au/TechnicalResources/ActuaryJournals.aspxen_HK
dc.relation.ispartofAustralian Actuarial Journalen_HK
dc.subjectNonparametric Bayesian credibility-
dc.subjectRisk characteristic of policyholder-
dc.subjectRandom probability distribution-
dc.subjectCredibility premium principle-
dc.subjectDirichlet process-
dc.titleNonparametric Bayesian Credibilityen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1442-3065&volume=15&issue=2&spage=209&epage=230&date=2009&atitle=Nonparametric+Bayesian+Credibility-
dc.identifier.emailSiu, TK: Ken-Siu@efs.mq.edu.auen_HK
dc.identifier.emailYang, H: hlyang@hkusua.hku.hk-
dc.identifier.authorityYang, H=rp00826en_HK
dc.identifier.hkuros173060en_HK
dc.identifier.volume15en_HK
dc.identifier.issue2en_HK
dc.identifier.spage209en_HK
dc.identifier.epage230en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats