pricing derivatives

State of the IT

To speed up the models produced by its SciFinance automated coding application for rapidly developing Monte Carlo or partial differential equation-based derivatives pricing and risk models, the company introduced the automatic generation of OpenMP or Nvidia CUDA-enabled parallel code. CUDA-based code runs on Nvidia's graphics processors 30-100 times faster than serial code on a standard PC, the company claims. It is also applicable to a range of Monte Carlo pricing models, including those with complex path dependency and Bermudan exercise features. SciCalibrator translates pricing model calibration specifications into C/C++ source code for use with a given model or as a stand-alone routine.

This article appeared in Risk Magazine

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Software vendors and service providers ease GPU adoption

...this approach masks the complexity of parallel programming from the end user, leaving them free to define the characteristics of the pricing model that they want to run on GPUs.