SciFinance contributes to the bottom line
Unlike typical modeling systems, SciFinance is not an inflexible set of library routines that offers imprecise or limited functionality for describing your pricing and risk model. Rather, SciFinance provides a concise, flexible, and extensible language to specify models in whatever terms best match your financial instruments. Its financial and mathematical constructs allow quantitative analysts and financial engineers to concisely describe the fundamentals of the financial instrument in terms similar to those they would use when describing the problem to a colleague, often with a few simple keywords.
This translates into significant contributions to the bottom line.
- Features cross asset class support
- Prices any financial derivative that can be valued with a PDE or SDE
- Offers complete model transparency, generating pricing model source code
- Enables you to make the modeling decisions: SciFinance is not a toolkit
- Generates CUDA-enabled or OpenMP compliant pricing model source code
- Reduces development time and risks
- Increases efficiency of quantitative developers
- Provides a common language to describe financial instruments
- Features easy integration with your existing trading and risk systems
SciFinance speeds time to market and reduces integration costs
SciFinance generates the pricing and risk model code for new derivative instruments in a matter of minutes. The open and transparent architecture of the system allows quantitative developers to formulate, test and refine alternative pricing and risk strategies at unprecedented speed. SciFinance-generated code can be seamlessly integrated with trading and risk systems. The process is made completely automatic with our integration tools. By simply adding a single line to an model specification, developers can automatically generate Microsoft Excel, COM, .NET, or Java interfaces. (customized interfaces also available). In addition, SciFinance does not impose any data model on the end user, which facilitates code integration.
SciFinance features broad asset class coverage
SciFinance can be used to develop pricing models for the full range of asset classes. SciFinance includes hundreds of existing model specifications that quantitative analysts may select from when building a pricing and risk model. The possibilities are virtually unlimited because sets of partial differential equations (PDEs) and stochastic differential equations (SDEs) can be mixed with user-specified combinations of financial and contract features. Features such as early exercise, forward starts and Asian tails, volatility surfaces, stochastic volatility, and jump diffusions are among those easily handled.
SciFinance improves efficiency
Financial engineers access cutting edge numerical methodologies and routines through keywords, not by writing a lengthy series of numerical equations and instructions. Quantitative analysts spend less time writing model specifications and hand coding the models and more time testing, evaluating and understanding the potential risk exposure of the pricing model.
Parallel codes speed model execution and reduce development and operational costs
SciFinance automatically generates parallel code styles. By harnessing the power of NVIDIA CUDA-enabled GPUs or multi-CPU workstations, SciFinance parallel codes run blazingly fast. SciFinance CUDA-enabled codes achieve astounding accelerations, while SciFinance OpenMP-compliant codes yield near linear acceleration on multi-CPU workstations.
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