The Solvency II directive asks insurance companies to derive their solvency capital requirement from the full loss distribution over the coming year. While this is in general computationally infeasible in the life insurance business, an application of the Least-Squares Monte Carlo (LSMC) method...

The least-squares Monte Carlo method has proved to be a suitable approximation technique for the calculation of a life insurer's solvency capital requirements. We suggest to enhance it by the use of a neural network based approach to construct the proxy function that models the insurer's loss...

Under the Solvency II regime, life insurance companies are asked to derive their solvency capital requirements from the full loss distributions over the coming year. Since the industry is currently far from being endowed with sufficient computational capacities to fully simulate these...

1. Introduction and user guide -- 2. Generating random numbers -- 3. The Monte Carlo method : basic principles -- 4. Continuous-time stochastic processes : continuous paths -- 5. Simulating financial models : continuous paths -- 6. Continuous-time stochastic processes : discontinuous paths -- 7....

Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including...