Multivariate almost stochastic dominance

<?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">MAP20180020087</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20180828145715.0</controlfield>
    <controlfield tag="008">180702e20180601usa|||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">MAPA20180009372</subfield>
      <subfield code="a">Tsetlin, Ilia</subfield>
    </datafield>
    <datafield tag="245" ind1="1" ind2="0">
      <subfield code="a">Multivariate almost stochastic dominance</subfield>
      <subfield code="c">Ilia Tsetlin, Robert L. Winkler</subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">Almost stochastic dominance allows small violations of stochastic dominance rules to avoid situations where most decision makers prefer one alternative to another but stochastic dominance cannot rank them. We present the concepts of multivariate almost stochastic dominance and multivariate almost nth-degree risk and their connections with a preference for combining good with bad. Then, we show how a preference for combining good with bad can be applied to obtain various comparative statics results, and we extend our approach to risk-prone (convex) stochastic dominance, which relates to the opposite preference, for combining good with good and bad with bad</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20090039629</subfield>
      <subfield code="a">Riesgo actuarial</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080588953</subfield>
      <subfield code="a">Análisis de riesgos</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080586447</subfield>
      <subfield code="a">Modelo estocástico</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080602437</subfield>
      <subfield code="a">Matemática del seguro</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080592011</subfield>
      <subfield code="a">Modelos actuariales</subfield>
    </datafield>
    <datafield tag="700" ind1="1" ind2=" ">
      <subfield code="0">MAPA20150011510</subfield>
      <subfield code="a">Winkler, Robert L.</subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20077000727</subfield>
      <subfield code="t">The Journal of risk and insurance</subfield>
      <subfield code="d">Nueva York : The American Risk and Insurance Association, 1964-</subfield>
      <subfield code="x">0022-4367</subfield>
      <subfield code="g">01/06/2018 Volumen 85 Número 2 - junio 2018 , p. 431-445</subfield>
    </datafield>
  </record>
</collection>