SyMBOL is a micro-funded statistical tool which analyses the consequences of bank failures and is used by the European Commission to assess regulatory proposals to enhance financial stability and prevent future financial crises. At the core of the model, there is a Monte Carlo simulation applying the Basel Foundation Internal Rating Based loss distribution. For security reasons, we were asked not to use our server where the C code is usually run. This forced us to re-code SyMBOL and we opted to do this in Julia. We considered different design options and faced the issue that results must be exactly the same. Our current design uses the main process to generate the random numbers, while the remote processes fetch the random numbers to calculate the correlated random shocks and check whether a bank has defaulted. The simulations stop if a pre-set number of runs (usually 100.000 runs) have at least one defaulted bank. Given this set up and the parallel computing capabilities of Julia we were able to reduce the computing time by around 50% compared to the parallel C-code discussed in Muresano and Pagano (2016). Muresano, R., Pagano, A., 2016. Adapting and Optimizing the Systemic Model of Banking Originated Losses (SYMBOL) Tool to the Multi-core Architecture. Comput. Econ. 48, 253–280. doi:10.1007/s10614-015-9509-4
