Claims reserving with a stochastic vector projection

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<title>Claims reserving with a stochastic vector projection</title>
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<name type="personal" usage="primary" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080112387">
<namePart>Portugal, Luis</namePart>
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<namePart>Pantelous, Athanasios A.</namePart>
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<abstract displayLabel="Summary">In the last three decades, a variety of stochastic reserving models have been proposed in the general insurance literature mainly using (or reproducing) the well-known Chain-Ladder claims-reserving estimates. In practice, when the data do not satisfy the Chain-Ladder assumptions, high prediction errors might occur. Thus, in this article, a combined methodology is proposed based on the stochastic vector projection method and uses the regression through the origin approach of Murphy, but with heteroscedastic errors instead, and different from those that used by Mack. Furthermore, the Mack distribution-free model appears to have higher prediction errors when compared with the proposed one, particularly, for data sets with increasing (regular) trends. Finally, three empirical examples with irregular and regular data sets illustrate the theoretical findings, and the concepts of best estimate and risk margin are reported.</abstract>
<note type="statement of responsibility">Luís Portugal, Athanasios A. Pantelous, Hirbod Assa</note>
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<topic>Modelo estocástico</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080602437">
<topic>Matemática del seguro</topic>
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<topic>Modelos predictivos</topic>
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<topic>Modelos estadísticos</topic>
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<topic>Modelos matemáticos</topic>
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<topic>Predicciones estadísticas</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080582340">
<topic>Reservas técnicas</topic>
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<title>North American actuarial journal</title>
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<publisher>Schaumburg : Society of Actuaries, 1997-</publisher>
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<identifier type="issn">1092-0277</identifier>
<identifier type="local">MAP20077000239</identifier>
<part>
<text>05/03/2018 Tomo 22 Número 1 - 2018 , p. 22-39</text>
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