Regression modeling for the valuation of large variable annuity portfolios

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<rdf:Description>
<dc:creator>Gan, Guojun</dc:creator>
<dc:creator>Valdez, Emiliano A.</dc:creator>
<dc:date>2018-03-01</dc:date>
<dc:description xml:lang="es">Sumario: Variable annuities are insurance products that contain complex guarantees. To manage the financial risks associated with these guarantees, insurance companies rely heavily on Monte Carlo simulation. However, using Monte Carlo simulation to calculate the fair market values of these guarantees for a large portfolio of variable annuities is extremely time consuming. In this article, we propose the class of GB2 distributions to model the fair market values of guarantees to capture the positive skewness typically observed empirically. Numerical results are used to demonstrate and evaluate the performance of the proposed model in terms of accuracy and speed</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/164661.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Productos de seguros</dc:subject>
<dc:subject xml:lang="es">Empresas de seguros</dc:subject>
<dc:subject xml:lang="es">Simulación Monte Carlo</dc:subject>
<dc:subject xml:lang="es">Valor de mercado</dc:subject>
<dc:subject xml:lang="es">Rendimiento</dc:subject>
<dc:subject xml:lang="es">Matemática del seguro</dc:subject>
<dc:subject xml:lang="es">Modelos de simulación</dc:subject>
<dc:subject xml:lang="es">Modelo estocástico</dc:subject>
<dc:subject xml:lang="es">Modelos matemáticos</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Regression modeling for the valuation of large variable annuity portfolios</dc:title>
<dc:relation xml:lang="es">En: North American actuarial journal. - Schaumburg : Society of Actuaries, 1997- = ISSN 1092-0277. - 05/03/2018 Tomo 22 Número 1 - 2018 , p. 40-54</dc:relation>
</rdf:Description>
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