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A Form of multivariate pareto distribution with applications to financial risk measurement

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      <subfield code="a">Su, Jianxi</subfield>
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      <subfield code="a">A Form of multivariate pareto distribution with applications to financial risk measurement</subfield>
      <subfield code="c">Jianxi Su, Edward Furman</subfield>
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      <subfield code="a">A new multivariate distribution possessing arbitrarily parametrized and positively dependent univariate Pareto margins is introduced. Unlike the probability law of Asimit et al. (2010), the structure in this paper is absolutely continuous with respect to the corresponding Lebesgue measure. The distribution is of importance to actuaries through its connections to the popular frailty models, as well as because of the capacity to describe dependent heavy-tailed risks. The genesis of the new distribution is linked to a number of existing probability models, and useful characteristic results are proved. Expressions for, e.g., the decumulative distribution and probability density functions, (joint) moments and regressions are developed. The distributions of minima and maxima, as well as, some weighted risk measures are employed to exemplify possible applications of the distribution in insurance.</subfield>
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      <subfield code="a">Matemática del seguro</subfield>
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      <subfield code="0">MAPA20080604721</subfield>
      <subfield code="a">Análisis multivariante</subfield>
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      <subfield code="0">MAPA20080582418</subfield>
      <subfield code="a">Riesgo financiero</subfield>
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      <subfield code="0">MAPA20080588953</subfield>
      <subfield code="a">Análisis de riesgos</subfield>
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      <subfield code="0">MAPA20100003213</subfield>
      <subfield code="a">Furman, Edward</subfield>
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      <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">02/01/2017 Volumen 47 Número 1 - enero 2017 , p. 331-357</subfield>
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