Stochastic Analysis of General Insurance Claims Using Markov Chain Monte Carlo Method

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dc.contributor.authorOssei Kofi, Tuffuor
dc.date.accessioned2017-01-20T11:37:40Z
dc.date.accessioned2023-04-18T22:26:18Z
dc.date.available2017-01-20T11:37:40Z
dc.date.available2023-04-18T22:26:18Z
dc.date.issuedOctober, 2016
dc.descriptionA thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the Degree of Master of Science in Actuarial Science.en_US
dc.description.abstractMotor insurance companies need to utilize past and current claim amounts in predicting future liabilities. It is therefore necessary that, motor insurance com- panies develop actuarial models using Bayesian and Markov Chain and Monte Carlo procedures. This thesis focuses on developing stochastic models for insur- ance claim amounts using Bayesian statistics. Motor insurance claim numbers usually follow compound Poisson distribution. This research work, however ex- amines the claim amount distributions. The methodology requires intensive use of Bayesian and Markov Chain Monte Carlo techniques through a software called WinBUGS. Two distributions usually tted to claim amounts are examined and the issues encountered when using Bayesian and Markov Chain Monte Carlo techniques in this context are investigated.en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/10089
dc.language.isoenen_US
dc.titleStochastic Analysis of General Insurance Claims Using Markov Chain Monte Carlo Methoden_US
dc.typeThesisen_US
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