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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Calvet Liñán, Laura | - |
dc.contributor.author | Lopeman, Madeleine | - |
dc.contributor.author | de Armas, Jesica | - |
dc.contributor.author | Franco, Guillermo | - |
dc.contributor.author | Juan, Angel A. | - |
dc.contributor.other | Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3) | - |
dc.contributor.other | Guy Carpenter & Company, LLC | - |
dc.contributor.other | Universitat Pompeu Fabra | - |
dc.date.accessioned | 2018-05-24T08:22:56Z | - |
dc.date.available | 2018-05-24T08:22:56Z | - |
dc.date.issued | 2017-07 | - |
dc.identifier.citation | Calvet-Liñan, L., Lopeman, M., de Armas Adrián, J., Franco, G. & Juan, A.A. (2017). Statistical and machine learning approaches for the minimization of trigger errors in earthquake catastrophe bonds. SORT: Statistics and Operations Research Transactions, 41(2), 1-20. doi: 10.2436/20.8080.02.64 | - |
dc.identifier.issn | 1696-2281MIAR | - |
dc.identifier.uri | http://hdl.handle.net/10609/78828 | - |
dc.description.abstract | Catastrophe bonds are financial instruments designed to transfer risk of monetary losses arising from earthquakes, hurricanes, or floods to the capital markets. The insurance and reinsurance industry, governments, and private entities employ them frequently to obtain coverage. Parametric catastrophe bonds base their payments on physical features. For instance, given parameters such as magnitude of the earthquake and the location of its epicenter, the bond may pay a fixed amount or not pay at all. This paper reviews statistical and machine learning techniques for designing trigger mechanisms and includes a computational experiment. Several lines of future research are discussed. | en |
dc.language.iso | eng | - |
dc.publisher | SORT: Statistics and Operations Research Transactions | - |
dc.relation.ispartof | SORT: Statistics and Operations Research Transactions, 2017, 41(2) | - |
dc.relation.uri | https://doi.org/10.2436/20.8080.02.64 | - |
dc.rights | CC BY-NC-ND | - |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | - |
dc.subject | catastrophe bonds | en |
dc.subject | risk of natural hazards | en |
dc.subject | classification techniques | en |
dc.subject | earthquakes | en |
dc.subject | insurance | en |
dc.subject | bons de catàstrofe | ca |
dc.subject | bonos catástrofe | es |
dc.subject | risc d'amenaces naturals | ca |
dc.subject | riesgo de amenazas naturales | es |
dc.subject | tècniques de classificació | ca |
dc.subject | técnicas de clasificación | es |
dc.subject | terratrèmols | ca |
dc.subject | terremotos | es |
dc.subject | assegurança | ca |
dc.subject | seguro | es |
dc.subject.lcsh | Computer science -- Statistics | en |
dc.title | Statistical and machine learning approaches for the minimization of trigger errors in earthquake catastrophe bonds | en |
dc.type | info:eu-repo/semantics/article | - |
dc.audience.mediator | Theme areas::Computer Science, Technology and Multimedia | en |
dc.subject.lemac | Informàtica -- Estadística | ca |
dc.subject.lcshes | Informática -- Estadística | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.doi | 10.2436/20.8080.02.64 | - |
dc.gir.id | AR/0000005877 | - |
dc.relation.projectID | TRA2013-48180-C3-P | - |
dc.relation.projectID | TRA2015-71883-REDT | - |
dc.relation.projectID | 2016-1-ES01-KA108-023465 | - |
dc.type.version | info:eu-repo/semantics/publishedVersion | - |
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