Search

The Efficient computation and the sensitivity analysis of finite-time ruin probabilities and the estimation of risk-based regulatory capital

<?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">MAP20160024210</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20160809150032.0</controlfield>
    <controlfield tag="008">160808e20160502usa|||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="1" ind2=" ">
      <subfield code="0">MAPA20160009897</subfield>
      <subfield code="a">Joshi, Mark S.</subfield>
    </datafield>
    <datafield tag="245" ind1="1" ind2="4">
      <subfield code="a">The Efficient computation and the sensitivity analysis of finite-time ruin probabilities and the estimation of risk-based regulatory capital</subfield>
      <subfield code="c">Mark S. Joshi, Dan Zhu</subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">Solvency regulations require financial institutions to hold initial capital so that ruin is a rare event. An important practical problem is to estimate the regulatory capital so the ruin probability is at the regulatory level, typically with less than 0.1% over a finite-time horizon. Estimating probabilities of rare events is challenging, since naive estimations via direct simulations of the surplus process is not feasible. In this paper, it is presents a stratified sampling algorithm for estimating finite-time ruin probabilities. It is then estimates the regulatory capital and its sensitivities. These estimates provide information to insurance companies for meeting prudential regulations as well as designing risk management strategies. Numerical examples are presented for the classical model, the Sparre Andersen model with interest and the periodic risk model with interest to demonstrate the speed and efficacy</subfield>
    </datafield>
    <datafield tag="700" ind1="1" ind2=" ">
      <subfield code="0">MAPA20160009903</subfield>
      <subfield code="a">Zhu, Dan</subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20077000420</subfield>
      <subfield code="t">Astin bulletin</subfield>
      <subfield code="d">Belgium : ASTIN and AFIR Sections of the International Actuarial Association</subfield>
      <subfield code="x">0515-0361</subfield>
      <subfield code="g">02/05/2016 Volumen 46 Número 2 - mayo 2016 , p. 431-467</subfield>
    </datafield>
  </record>
</collection>