Finance: High-Performance Computing
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 the Wolfram Language and the use of stochastic differential equations (SDEs) to describe customized derivatives with additional features such as stochastic volatility and stochastic interest rates.
Featured Products & Technologies: Wolfram Language, Mathematica
The course requires experience with programming in the Wolfram Language and knowledge of computational finance.
|This course is available on demand (36:07)||Free|
|This course is not currently scheduled.|
- 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