加速分级信用衍生品组合的计算

Stephen Weston, Jean-Tristan Marin, James Spooner, O. Pell, O. Mencer
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引用次数: 30

摘要

过去5年,信用衍生工具的交易和复杂性大幅增长,推动了对计算要求越来越高的数学模型的需求。这导致了数据中心计算能力、电力和冷却需求的大幅增长。我们报告了摩根大通和专业加速解决方案提供商Maxeler Technologies正在进行的联合项目的结果,该项目旨在改善计算大型复杂信用衍生品组合的价值和风险的性价比。我们的研究结果表明,与使用标准多核英特尔至强处理器的解决方案相比,在Maxeler加速系统上评估抵押违约债券(cdo)的每立方英尺和每瓦速度快30倍以上。我们还报告了将该方法扩展到利率衍生品类别的进一步工作的一些初步结果。
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Accelerating the computation of portfolios of tranched credit derivatives
Huge growth in the trading and complexity of credit derivative instruments over the past five years has driven the need for ever more computationally demanding mathematical models. This has led to massive growth in data center compute capacity, power and cooling requirements. We report the results of an on-going joint project between J.P. Morgan and specialist acceleration solutions provider Maxeler Technologies to improve the price-performance for calculating the value and risk of a large complex credit derivatives portfolio. Our results show that valuing tranches of Collateralized Default Obligations (CDOs) on Maxeler accelerated systems is over 30 times faster per cubic foot and per Watt than solutions using standard multi-core Intel Xeon processors. We also report some preliminary results of further work that extends the approach to classes of interest rate derivatives.
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Option pricing with the SABR model on the GPU Pricing structured equity products on GPUs Opportunities for shared memory parallelism in financial modeling Accelerating the computation of portfolios of tranched credit derivatives Adding stream processing system flexibility to exploit low-overhead communication systems
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