Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492180
Title: Dependent risk modelling in (re)insurance and ruin
Author: Dimitrova, Dimitrina S.
Awarding Body: City University London
Current Institution: City, University of London
Date of Award: 2007
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Abstract:
The work presented in this· dissertation is motivated by the· observation that the classical (re)insurance risk modelling assumptions of independent and identically distributed claim amounts, ~oisson claim arrivals and premium income accumulati~g linearly at a certain'rate, starting from possibly non-zero initial capital, are often not realistic and violated in practice. There is an abundance of examples in which dependence is observed at various levels ofthe underlying risk model. Developing risk models which are more general than the .classical one and can successfully incorporate dependence between claim amounts, consecutively arriving at the insurance company, and/or dependence between the claim inter-arrival times, is at. the heart of this dissertation. The main objective is to consider such general models and to address the problem of (non-) ruin within a finite-time horizon of an insurance company. Furthermore, the aim is to consider general risk and performance measures in the context of a risk sharing arrangement such as an excess of loss (XL) reinsurance contract. There are two parties involved in an XL reinsurance contract and their interests are contradictory, as has been first noted bYI Karl Borch in the 1960s. Therefore, we define joint,· between the cedent mid the reinsurer,· risk and performance measures, both based on the probability of ruin, and show how the latter can be used to optimally set the parameters of an XL reinsurance treaty. Explicit expressions for the proposed risk and performance measures are derived and are used efficiently in numerical illustrations.
Supervisor: Not available Sponsor: Not available
Qualification Name: City University London, 2007 Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.492180  DOI: Not available
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