Búsqueda

Efficient simulation designs for valuation of large variable annuity portfolios

<?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">MAP20200018124</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20200602122615.0</controlfield>
    <controlfield tag="008">200528e20200601usa|||p      |0|||b|eng 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">6</subfield>
    </datafield>
    <datafield tag="100" ind1=" " ind2=" ">
      <subfield code="0">MAPA20200012627</subfield>
      <subfield code="a">Mingbin Feng, Ben </subfield>
    </datafield>
    <datafield tag="245" ind1="1" ind2="0">
      <subfield code="a">Efficient simulation designs for valuation of large variable annuity portfolios</subfield>
      <subfield code="c">Ben Mingbin Feng , Zhenni Tan, Jiayi Zheng</subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">The valuation of large variable annuity portfolios is an important enterprise risk management task but is computationally challenging due to the need for simulation. Existing methods in the literature only use simple experimental designs with significant room for improvement. This article identifies three major components in an efficient valuation framework. In addition, we propose optimal experimental designs and provides analytical insights for each component. Our numerical results show that our proposal achieves significantly higher accuracy than state-of-the-art alternatives without requiring any additional computational resource.</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080599126</subfield>
      <subfield code="a">Simulación económica</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080602642</subfield>
      <subfield code="a">Modelos de simulación</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080618766</subfield>
      <subfield code="a">Valoración de inversiones</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080591182</subfield>
      <subfield code="a">Gerencia de riesgos</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080591953</subfield>
      <subfield code="a">Métodos actuariales</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080555993</subfield>
      <subfield code="a">Propuestas</subfield>
    </datafield>
    <datafield tag="700" ind1="1" ind2=" ">
      <subfield code="0">MAPA20200012672</subfield>
      <subfield code="a">Tan, Zhenni </subfield>
    </datafield>
    <datafield tag="700" ind1="1" ind2=" ">
      <subfield code="0">MAPA20200012689</subfield>
      <subfield code="a">Zheng, Jiayi </subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20077000239</subfield>
      <subfield code="t">North American actuarial journal</subfield>
      <subfield code="d">Schaumburg : Society of Actuaries, 1997-</subfield>
      <subfield code="x">1092-0277</subfield>
      <subfield code="g">01/06/2020 Tomo 24 Número 2 - 2020 , p. 275-289</subfield>
    </datafield>
  </record>
</collection>