Modeling multi-country mortality dependence and its application in princig survivor index swaps-a dynamic copula approach

<?xml version="1.0" encoding="UTF-8"?><modsCollection xmlns="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-8.xsd">
<mods version="3.8">
<titleInfo>
<title>Modeling multi-country mortality dependence and its application in princig survivor index swaps-a dynamic copula approach</title>
</titleInfo>
<typeOfResource>text</typeOfResource>
<genre authority="marcgt">periodical</genre>
<originInfo>
<place>
<placeTerm type="code" authority="marccountry">esp</placeTerm>
</place>
<dateIssued encoding="marc">2015</dateIssued>
<issuance>serial</issuance>
</originInfo>
<language>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</language>
<physicalDescription>
<form authority="marcform">print</form>
</physicalDescription>
<abstract displayLabel="Summary">This paper introduces mortality dependence in multi-country mortality modeling using a dynamic copula approach. Specifically, we use time-varying copula models to capture the mortality dependence structure across countries, examining both symmetric and asymmetric dependence structures. In addition, to capture the phenomenon of a heavy tail for the multi-country mortality index, we consider not only the setting of Gaussian innovations but also non-Gaussian innovations under the Lee-Carter framework model. As tests of the goodness of fit of different dynamic copula models, the pattern of mortality dependence, and the distribution of the innovations, we used empirical mortality data from Finland, France, the Netherlands, and Sweden. To understand the effect of mortality dependence on longevity derivatives, we also built a valuation framework for pricing a survivor index swap, then investigated the fair swap rates of a survivor swap numerically. We demonstrate that failing to consider the dynamic copula mortality model and non-Gaussian innovations would lead to serious underestimations of the swap rates and loss reserves.</abstract>
<note type="statement of responsibility">Chou-Wen Wang, Sharon S. Yang, Hong-Chih Huang</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555306">
<topic>Mortalidad</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080576790">
<topic>Modelo Gaussiano</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20090035034">
<topic>Modelización mediante cópulas</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555016">
<topic>Longevidad</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080586447">
<topic>Modelo estocástico</topic>
</subject>
<classification authority="">6</classification>
<relatedItem type="host">
<titleInfo>
<title>Insurance : mathematics and economics</title>
</titleInfo>
<originInfo>
<publisher>Oxford : Elsevier, 1990-</publisher>
</originInfo>
<identifier type="issn">0167-6687</identifier>
<identifier type="local">MAP20077100574</identifier>
<part>
<text>27/08/2015 Volumen 63 - julio 2015 , p. 30-39</text>
</part>
</relatedItem>
<recordInfo>
<recordContentSource authority="marcorg">MAP</recordContentSource>
<recordCreationDate encoding="marc">150831</recordCreationDate>
<recordChangeDate encoding="iso8601">20150914101136.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20150027856</recordIdentifier>
<languageOfCataloging>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</languageOfCataloging>
</recordInfo>
</mods>
</modsCollection>