A Gray T3E implementation of a parallel stochastic dynamic assets and liabilities management model

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 compu ter resources - may be much more useful if a dynamic stochastic simulation is adopted. This makes it possible to increase the precision of risk estima tion. In this paper the parallelization strategy adopted to implement such a stochastic ALM code is described, together with porting and code performa nce issues. The very good timings obtained on a 128-proc Gray T3E are repor ted, Anyway the code is easily portable on other, possibly heterogeneous, h igh-performance computing platforms, (C) 2000 Elsevier Science B.V. All rig hts reserved.