A Hybrid method to evaluate pure endowment policies : crédit Agricole and ERGO Index linked policies

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<title>Hybrid method to evaluate pure endowment policies</title>
<subTitle>: crédit Agricole and ERGO Index linked policies</subTitle>
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<namePart>Recchioni, M.C.</namePart>
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<abstract>An empirical method to evaluate pure endowment policies is proposed. The financial component of the policies is described using the time dependent Black Scholes model and making a suitable choice for its time dependent parameter functions. Specifically, the integral of the time dependent risk free interest rate is modeled using an extension of the Nelson and Siegel yield curve (see Dielbold and Li, 2006). The time dependent volatility is expressed using two different models. One of these is based on an extension of the Nelson and Siegel model (Dielbold and Li, 2006), while the other assumes that the volatility is a piecewise function with respect to the time variable. The demographic component is modeled using a generalization of the geometric Brownian mean reverting Gompertz model while an asymptotic formula for survival probability is derived when the mortality risk volatility is small. The method has been tested on two policies. In these the risk free interest rate parameters are calibrated using the one-month, three-month, six-month, one-year, three-year and five-year US treasury constant maturity yields and the parameters of the volatility are calibrated using the VSTOXX volatility indices. The choice of the data employed in the calibration depends on the policy to be evaluated. The performance of the method is established comparing the observed values of the policies with the values obtained using this method.

<note type="statement of responsibility">M.C. Recchioni, F. Screpante</note>
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<title>Insurance : mathematics and economics</title>
<publisher>Oxford : Elsevier, 1990-</publisher>
<identifier type="issn">0167-6687</identifier>
<identifier type="local">MAP20077100574</identifier>
<text>07/07/2014 Volumen 57 Número 1 - julio 2014 </text>
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