FPGA Acceleration of Monte-Carlo Based Credit Derivative Pricing

Provided by: University of Toronto Topic: Hardware Date Added: Mar 2008 Format: PDF
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. The authors explore the precision requirements and the resulting resource utilization for each number representation. Their results show that their 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.

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