FPGA acceleration of Monte-Carlo based credit derivative pricing

Abstract

In recent years the financial world has seen an increasing demand for faster risk simulations, driven by growth in client portfolios. Traditionally many financial models employ Monte-Carlo simulation, which can take excessively long to compute in software. This paper describes a hardware implementation for collateralized debt obligations (CDOs) pricing, using the one-factor Gaussian copula (OFGC) model. We explore the precision requirements and the resulting resource utilization for each number representation. Our results show that our hardware implementation mapped onto a Xilinx XC5VSX50T is over 63 times faster than a software implementation running on a 3.4 GHz Intel Xeon processor.