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Finance: High-Performance Computing in Finance

This course covers CUDAFinancialDerivative and its ongoing extensions to include all the options handled by FinancialDerivative. Other topics include the use of SymbolicC to allow for the creation of GPU code from Mathematica and the use of stochastic differential equations (SDEs) to describe customized derivatives with additional features such as stochastic volatility and stochastic interest rates.

Level: Advanced

The course requires experience with programming in Mathematica and knowledge of computational finance.

On Demand
This course is available on demand (36:07) Free
Live
This course is not currently scheduled.

Outline

  • Introduction to CUDAFinancial Derivative and parallelization
  • Case Study: Finance—Code Generation
  • A primer on CUDA Brownian motion
  • Simulation of stochastic differential equations
  • Implementing stochastic volatility and rate models
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