A Cray T3E implementation of a parallel stochastic dynamic assets and liabilities management model (Q1978669)

Asset and Liability Management (ALM) models represent an important tool for banks and finance companies to measure the volatility of expected revenues. These models -- usually static and deterministic to fit conventional computer resources -- may be much more useful if a dynamic stochastic simulation is adopted. This makes it possible to increase the precision of risk estimation. In this paper the parallelization strategy adopted to implement such a stochastic ALM code is described, together with porting and code performance issues. The very good timings obtained on a 128-proc Cray T3E are reported. Anyway the code is easily portable on other, possibly heterogeneous, high-performance computing platforms.