Computational Finance on the GPU

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Backoffice • Monitoring the banks exposure • Model all trades – Value – Risk • Value-at-Risk (VaR) required for regulation Traders Backoffice Quants Developers
Quants • Develop and implement models for traders • Develop independent models for validation • Research • Modelling exposure and capital Traders Backoffice Quants Developers
Page 1 and 2: Computational <str
Page 3 and 4: AGENDA Financial Instruments Who’
Page 5 and 6: Financial Instruments Cash Instrume
Page 7 and 8: Commodities • Raw resource - Agri
Page 9 and 10: Foreign Exchange • Also: Forex or
Page 11 and 12: Example: Options • Holder has the
Page 13: Traders • Trading: - Standardised
Page 19 and 20: Traders • Determine price for tra
Page 23 and 24: Binomial Trees • Represent possib
Page 25 and 26: Binomial Trees
Page 27 and 28: Finite Differences • Solve the Pa
Page 29 and 30: Finite Differences - Explicit • R
Page 31 and 32: Explicit Finite Differences on the
Page 33 and 34: Monte Carlo • Sample a random wal
Page 35 and 36: Monte Carlo on the GPU Generate Ran
Page 37 and 38: Monte Carlo - Single Kernel parfor
Page 39 and 40: Software legacy • Millions of lin
Page 41 and 42: Case Study: Equity Derivatives 15 1
Page 43 and 44: Case Study: Real-time Options 1 Sam
Page 47: Resources • GTC presentations - <

Computational Finance on the GPU

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