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Tuesday, July 28 • 4:00pm - 4:30pm
Performance Assessment of Real-time Estimation of Continuous-time Stochastic Volatility of Financial Data on GPUs

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Realtime Bayes estimation of stochastic volatility for financial ultra-high frequency data is plagued with the curse of high dimensionality. Methods have been developed to manage this problem through the use a parallel computing, relying on supercomputering and GPU resources. In the technical paper, we endeavour to assess the performance of GPU computing and show that an adequately equipped GPU workstation can rise to the task, producing reasonably realtime results with actual data from financial markets.

Tuesday July 28, 2015 4:00pm - 4:30pm CDT
Majestic C

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