Pricing structured equity products on GPUs

A. Bernemann, R. Schreyer, K. Spanderen
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引用次数: 15

Abstract

Pricing and risk analysis for today's structured equity products is computationally more and more demanding and time consuming. GPUs offer the possibility to significantly increase computing performance even at reduced costs. We applied this technology to replace a large amount of our CPU based computing grid by hybrid GPU/CPU pricing engines. One GPU based pricing engine with two Tesla C1060 replaced 140 CPU cores in performing Monte Carlo based simulation of our productive structured equity portfolio with the local and stochastic volatility model.
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gpu上结构性股票产品的定价
如今,结构性股票产品的定价和风险分析在计算上要求越来越高,耗时越来越长。gpu提供了在降低成本的情况下显著提高计算性能的可能性。我们应用这项技术用GPU/CPU混合定价引擎取代了大量基于CPU的计算网格。一个基于GPU的定价引擎和两个Tesla C1060取代了140个CPU内核,用本地和随机波动模型对我们的生产性结构化股票投资组合进行了基于蒙特卡罗的模拟。
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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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