Having previously discussed the core Xcelerit SDK, this series of posts will look into an addon targeted at a specific application domain: Quantitative Finance. It is aimed at helping quantitative analysts and financial engineers with their day-to-day work. The Xcelerit Quant addon consists of a set of provided statistics functions and extensions for commonly used software packages:

- Statistics Extension (random number generators, statistical reductions, common statistical functions),
- MATLAB Extension (for interfacing to MATLAB), and
- Excel Extension (for interfacing to Microsoft Excel)

We will look into each of these extensions, starting with the Statistics Extension.

### Statistics Extension

#### Overview

In computational finance, almost all models and algorithms have a statistical component. For example, Monte-Carlo simulations require random numbers and statistical reductions (such as mean and variance computation), and other algorithms use statistical distribution functions (cummulative distribution or probability density functions, quantiles, etc). The Xcelerit Statistics Extension provides built-in optimised functions for the convenience of users. Note that developers can also choose to implement their own components.

As an example application, the following figure shows an Xcelerit dataflow graph for a general Monte-Carlo simulation, as it is often found in financial algorithms:

Read more