Financial analysts seeking a broad range of mathematical and statistical functionality important to financial product development and portfolio analysis without the considerable expense and bother of sourcing multiple Matlab toolboxes, can now access 1,415 rigorously tested numerical routines in the Mark 22 Release of the multipurpose NAG TOOLBOX FOR MATLAB.
This one-stop solution for the finance industry's computing needs also allows quantitative analysts to easily and confidently migrate prototype code developed in the MATLAB environment to final production code in advanced programming languages such as C or FORTRAN while still using the same robust algorithms. NAG is renowned for the quality of its documentation and example programs to assist users. In addition, this release of the NAG TOOLBOX FOR MATLAB includes more than a dozen quickly accessible MATLAB-based examples of advanced programming for optimization problems, simulations, time series analyses and other functions important to financial engineering.
NAG TOOLBOX FOR MATLAB is available for both Linux and Microsoft Window.
Commenting on the algorithmic quality in the NAG TOOLBOX FOR MATLAB, Dr. Ning Guo of the University of Warwick, UK (an institution with world-renowned Finance, Engineering among other departments) said, "I am especially impressed by the optimization algorithms provided. One improves my maximum likelihood estimates where sample size is small causing non-concentration likelihood. Ordinary algorithms perform poorly."
David Cassell, Product Marketing Manager for the NAG organization comments, "Like all NAG products, the NAG TOOLBOX FOR MATLAB has been developed to help users safeguard and future proof their software investments. All the routines included in the NAG TOOLBOX FOR MATLAB were written by experts in their fields and rigorously tested for correctness, reliability and robustness. No other MATLAB toolbox can match the level of expert documentation included or the detailed example programs, - invaluable aids in selecting the right algorithm without wasting time."