Index for predicting insurance claims from wind storms with an application in France

<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
  <record>
    <leader>00000cab a2200000   4500</leader>
    <controlfield tag="001">MAP20160001129</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20160113170929.0</controlfield>
    <controlfield tag="008">160113e20151102esp|||p      |0|||b|spa d</controlfield>
    <datafield tag="040" ind1=" " ind2=" ">
      <subfield code="a">MAP</subfield>
      <subfield code="b">spa</subfield>
      <subfield code="d">MAP</subfield>
    </datafield>
    <datafield tag="084" ind1=" " ind2=" ">
      <subfield code="a">328.1</subfield>
    </datafield>
    <datafield tag="245" ind1="0" ind2="0">
      <subfield code="a">Index for predicting insurance claims from wind storms with an application in France</subfield>
      <subfield code="c">Alexandre Mornet...[et.al]</subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">For insurance companies, wind storms represent a main source of volatility, leading to potentially huge aggregated claim amounts. In this article, we compare different constructions of a storm index allowing us to assess the economic impact of storms on an insurance portfolio by exploiting information from historical wind speed data. Contrary to historical insurance portfolio data, meteorological variables show fewer nonstationarities between years and are easily available with long observation records; hence, they represent a valuable source of additional information for insurers if the relation between observations of claims and wind speeds can be revealed. Since standard correlation measures between raw wind speeds and insurance claims are weak, a storm index focusing on high wind speeds can afford better information. A storm index approach has been applied to yearly aggregated claim amounts in Germany with promising results. Using historical meteorological and insurance data, we assess the consistency of the proposed index constructions with respect to various parameters and weights. Moreover, we are able to place the major insurance events since 1998 on a broader horizon beyond 40 years. Our approach provides a meteorological justification for calculating the return periods of extreme-storm-related insurance events whose magnitude has rarely been reached.</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080629755</subfield>
      <subfield code="a">Seguro de riesgos extraordinarios</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080552800</subfield>
      <subfield code="a">Tormentas</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080542580</subfield>
      <subfield code="a">Viento</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080567118</subfield>
      <subfield code="a">Reclamaciones</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080621926</subfield>
      <subfield code="a">Predicciones meteorológicas</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20120011137</subfield>
      <subfield code="a">Predicciones estadísticas</subfield>
    </datafield>
    <datafield tag="651" ind1=" " ind2="1">
      <subfield code="0">MAPA20080637880</subfield>
      <subfield code="a">Francia</subfield>
    </datafield>
    <datafield tag="700" ind1="1" ind2=" ">
      <subfield code="0">MAPA20160001013</subfield>
      <subfield code="a">Mornet, Alexandre</subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20077000345</subfield>
      <subfield code="t">Risk analysis : an international journal</subfield>
      <subfield code="d">McLean, Virginia : Society for Risk Analysis, 1987-2015</subfield>
      <subfield code="x">0272-4332</subfield>
      <subfield code="g">02/11/2015 Volumen 35 Número 11 - noviembre 2015 , p. 2029-2056</subfield>
    </datafield>
  </record>
</collection>