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A Marked cox model for the number of ibnr claims : estimation and application

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<title>Marked cox model for the number of ibnr claims</title>
<subTitle>: estimation and application</subTitle>
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<genre authority="marcgt">periodical</genre>
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<dateIssued encoding="marc">2019</dateIssued>
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<abstract displayLabel="Summary">Incurred but not reported (IBNR) loss reserving is of great importance for Property & Casualty (P&C) insurers. However, the temporal dependence exhibited in the claim arrival process is not reflected in many current loss reserving models, which might affect the accuracy of the IBNR reserve predictions. To overcome this shortcoming, we proposed a marked Cox process and showed its many desirable properties in Badescu et al. (2016). In this paper, we consider the model estimation and applications. We first present an expectationmaximization (EM) algorithm which guarantees the efficiency of the estimators unlike the moment estimation methods widely used in estimating Cox processes. In addition, the proposed fitting algorithm can be implemented at a reasonable computational cost. We examine the performance of the proposed algorithm through simulation studies. The applicability of the proposed model is tested by fitting it to a real insurance claim data set. Through out-of-sample tests, we find that the proposed model can provide realistic predictive distributions.</abstract>
<note type="statement of responsibility">Andrei L. Badescu...[et.al.]</note>
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<topic>IBNR</topic>
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<topic>Modelo de Markov</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080579258">
<topic>Cálculo actuarial</topic>
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<topic>Reclamaciones</topic>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
<identifier type="local">MAP20077000420</identifier>
<part>
<text>02/09/2019 Volumen 49 Número 3 - septiembre 2019 , p. 709-739</text>
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<recordCreationDate encoding="marc">191106</recordCreationDate>
<recordChangeDate encoding="iso8601">20191106164440.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20190032100</recordIdentifier>
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