In this paper we discuss the development of a parallel software for the numerical simulation of Participating Life Insurance Policies on distributed architectures. The use of stochastic pricing models, together with the request of solutions in a "useful" time, which have to be sufficiently accurate for the financial problem as well, make the financial problem a very computationally intensive one; as a consequence, advanced architectures are mandatory for effective decisional processes. The mathematical models, which describe the considered problems, usually require the evaluation of multidimensional integrals and the solution of Stochastic Differential Equations. The involved integrals are solved by means of Monte Carlo method in conjunction with the Antithetic Variates variance reduction technique, while Differential Equations are approximated via a fully implicit Euler scheme. The parallelization strategy we adopt relies on the parallelization of Monte Carlo algorithm. We implement and test the software on cluster architectures.

Financial evaluation of participating life insurance policies in distributed environments

CORSARO, STEFANIA;DE ANGELIS, Pasquale Luigi;MARINO, ZELDA;PERLA, Francesca;ZANETTI, Paolo
2008

Abstract

In this paper we discuss the development of a parallel software for the numerical simulation of Participating Life Insurance Policies on distributed architectures. The use of stochastic pricing models, together with the request of solutions in a "useful" time, which have to be sufficiently accurate for the financial problem as well, make the financial problem a very computationally intensive one; as a consequence, advanced architectures are mandatory for effective decisional processes. The mathematical models, which describe the considered problems, usually require the evaluation of multidimensional integrals and the solution of Stochastic Differential Equations. The involved integrals are solved by means of Monte Carlo method in conjunction with the Antithetic Variates variance reduction technique, while Differential Equations are approximated via a fully implicit Euler scheme. The parallelization strategy we adopt relies on the parallelization of Monte Carlo algorithm. We implement and test the software on cluster architectures.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/2423
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