Credit Risk Modeling with MATLAB
Financial risk management is a substantial topic. The foundation of all risk measures is verified quantitative functionality, statistical rigor and an ability to integrate rapidly with existing systems and infrastructure.
In this new Credit Risk Modeling seminar, MathWorks financial engineers will illustrate how MATLAB can help risk teams build an agile Credit Risk Management infrastructure, using MATLAB’s advanced modeling, analysis and deployment tools to build risk analytics quickly and then implement into enterprise risk architectures. Whether risk is core to your job or if you are simply interest to build and deploy good quantitative analysis, this seminar will be ideal for you.
Please join us for this free event to learn why finance and risk professionals worldwide use MATLAB and the MathWorks suite of financial tools to conduct research, rapidly prototype risk models, and develop financial tools up to 90% more efficiently than with traditional programming languages.
http://bit.ly/953p3C
Starts
3/10/2010 @ 9:00
Ends
3/10/2010 @ 12:00
Location
Intercontinental Toronto Centre
225 Front Street West
Toronto, ON
Financial risk management is a substantial topic. The foundation of all risk measures is verified quantitative functionality, statistical rigor and an ability to integrate rapidly with existing systems and infrastructure.
In this new Credit Risk Modeling seminar, MathWorks financial engineers will illustrate how MATLAB can help risk teams build an agile Credit Risk Management infrastructure, using MATLAB’s advanced modeling, analysis and deployment tools to build risk analytics quickly and then implement into enterprise risk architectures. Whether risk is core to your job or if you are simply interest to build and deploy good quantitative analysis, this seminar will be ideal for you.
Please join us for this free event to learn why finance and risk professionals worldwide use MATLAB and the MathWorks suite of financial tools to conduct research, rapidly prototype risk models, and develop financial tools up to 90% more efficiently than with traditional programming languages.
http://bit.ly/953p3C