The NAG Blog

One of the questions I get asked most often while out and about in the HPC community at conferences, or visiting (prospective) customers is: "Who are your HPC consulting customers?".

The simple answer to that is most prefer to remain confidential, because they see a competitive advantage from using our HPC advice or services.
There are a few we are very proud to be able to name. For example NAG has worked with EPSRC to provide the Computational Science and Engineering Support Service as part of the HECToR national supercomputing service, and to provide independent expert advice on the technology options and procurement for the UK's national academic supercomputers (HECToR and ARCHER).
We enjoyed working with our friends at Red Oak Consulting to support the KAUSTShaheen II supercomputer procurement recently - see our joint press release.
There have been others that we have been able to name over the years. But, who are the confidential customers? Well, obviously I'm n…

In the latest NAG technical report we examine the main theoretical aspects in some models used in Portfolio credit risk. We introduce the well-known Vasicek model, the large homogeneous portfolios or Vasicek distribution and their corresponding generalizations. An illustrative example considering factors following a logistic distribution is presented. Numerical experiments for several homogeneous portfolios are performed in order to compare these methods. Finally, we use the NAG Toolbox for MATLAB® for implementing prototypes of these models quickly.

We described the most widely used models for the calculation of default probabilities in portfolio credit risk. We introduced the Vasicek one-factor model and its generalization for factors following non Normal distributions. Similarly, we presented the large portfolio approximation method and we generated closed-form expressions for the so-called general loss distribution. In section 7 we provide code for the main routines used through…