TIME VARYING SENSITIVITIES ON A GRID ARCHITECTURE

We investigate the gains obtained by using GRID, an innovative web-based technology for parallel computing, in a Risk Management application. We show, by estimating a parametric Value at Risk, how GRID computing offers an opportunity to enhance the solution of computationally demanding problems with decentralized data retrieval. Furthermore, we also provide an analysis of the risk factors in the US market, by empirically testing, on the Fama and French database, a classic one factor model augmented with a time varying specification of beta.