Issue 93, 11 November 2010
- NAG Library for .NET now available
- User Story: Morningstar use NAG Library routines to assist portfolio construction and optimization
- Exact First- and Second-Order Greeks by Algorithmic Differentiation
- Mathematics on the Web: MathML 3.0 recommendation
- NAG Training Courses: University of Bristol
- Recent NAG Blog Posts
- Out & About with NAG
- New NAG product implementations
NAG Library for .NET now available
The NAG Library for .NET contains mathematical and statistical methods developed by NAG experts to serve the growing number of application developers and users of Microsoft .NET. The methods provide a convenient interface to fast and efficient algorithms that enhance application capabilities and reduce crucial development time.
The use of the .NET development framework is becoming more widespread, particularly in the finance industry. It's gaining popularity due to quicker development times, its flexible nature and ease of deployment. NAG serves the growing number of users of the .NET framework by providing world-class mathematical and statistical methods to further support robust and reliable applications.
If you'd like to use the NAG Library for .NET email us for more information.
User Story: Morningstar use NAG Library routines to assist portfolio construction and optimization
Ibbotson Associates is a registered investment advisor and wholly owned subsidiary of Morningstar, Inc. providing asset allocation, manager selection and portfolio construction services to financial institutions.
The Ibbotson Associates proprietary investment methodology creates custom target maturity portfolios for financial institutions serving plans of all sizes in defined contribution markets. The stock-bond mix over time, or glidepath, is set using the optimization techniques appropriate to the unique characteristics of each particular plan's participants. Factors considered in selecting a glidepath include the existence of a defined benefit plan, employee tenure, employee risk capacity, savings rates, median salaries, and others.
Knowing that NAG develops world-class numerical routines for optimization, Morningstar chose the NAG Library after a period of evaluation. The optimization techniques in the NAG Library are utilised by Morningstar on a daily basis, in their portfolio construction products. When observing and analysing portfolios, a quadratic objective function is used to optimize risk and return. The objective function, together with business constraints and other fund analysis is then used by the NAG optimization functions to do the complex mathematics. Different tracking error weights and forward looking alphas are then run through the model to arrive at a frontier giving the selection of the optimal solutions which are then packaged for clients.
Read the full story.
Exact First- and Second-Order Greeks by Algorithmic Differentiation
NAG is currently working with Professor Uwe Naumann, Head of Group, LuFG Software and Tools for Computational Engineering at Aachen University to deliver automatic differentiation solutions.
Algorithmic (also known as Automatic) Differentiation (AD) is a method for computing sensitivities of outputs of numerical programs with respect to its inputs both accurately (to machine precision) and efficiently. The two basic modes of AD - forward and reverse - and combinations thereof yield products of a vector with the Jacobian, its transpose, or the Hessian, respectively.
Numerical simulation plays a central role in computational finance as well as computational science and engineering. Gradients, (projected) Jacobians, (projected) Hessians or even higher-order sensitivities are required in order to make the highly desirable transition from pure simulation to optimization of the numerical model or its parameters.
Continue reading the paper here.
David Carlisle, Principal Technical Consultant at NAG and leader of the XML Technologies Group has been part of the MathML project team for over 12 years. On 21 October the project team published MathML 3.0 as a W3C recommendation.
In his latest blog he writes about what the project team achieved in the seven years since the previous MathML recommendation, including additions to control bi-directional layout, elementary maths layouts, linebreaking of mathematics and more. So if you're interested in the display of mathematics on the web you'll find his blog post here.
NAG are giving training couses at the University of Bristol on 25 November 2010. If you'd like to attend either courses - please note that places are limited, and will be issued on a first come, first served basis - email Caroline Gardiner.
Training Course 1 'Multicore Demystified'
An Introduction to Multicore Programming and the NAG Library for SMP & multicore
10.00am-12noon- 25 November 2010
In this session we aim to demystify programming your multicore machine. We give an introduction to the terminology and what it really means. We give a brief introduction to the programming language OpenMP, the main language for shared memory machines. We also show you how to get the most out of the NAG Library for SMP & multicore with performance hints and tips.
Training Course 2 'Using the NAG Toolbox for MATLAB''
1.00pm-4.00pm - 25 November 2010
We will give an overview of the NAG Library and show how easy it is to access the power of the library from your MATLAB' code using the NAG Toolbox for MATLAB. There will be a hands-on session with exercises to help familiarise yourself with the Toolbox.
The session is aimed for those familiar with the basics of MATLAB who would like to know more about how the NAG Library can enhance your MATLAB applications.
Comparing HPC across China, USA and Europe
Why does the China supercomputer matter to western governments?
Source-level debugging of Python in Emacs
2010: A Retail Store Odyssey
The Shoulder of Giants
Out & About with NAG
15-18 November 2010, New Orleans
Multiple NAG experts will be attending this key event
- 2nd UK GPU Computing Conference
13-14 December 2010, Cambridge.
NAG is delighted to support this conference following on from the successful 1st event in Oxford last year.
- HECToR (High End Computing Terascale Resource) Training Courses
Presented by the NAG HECToR Team
A full list of forthcoming HECToR Training Courses can be viewed on the official HECToR website here.
For more information on any of the above events visit NAG's ‘Out & About’ webpage
New NAG product implementations
The NAG C Library, Mark 9 is now also available for the following platforms:
- Intel EM64T Windows64 using the Intel C compiler
The NAG Library for .NET, Release 1 is now available for the following platforms:
- 32 bit and 64 bit Windows
The NAG Fortran Compiler, Release 5.2 is now also available for the following platforms:
- Apple Intel Mac64 OS X
For full details of these and all other available implementations, visit the NAG site. Comprehensive technical details of each implementation are given in the relevant Installation and User Notes at http://www.nag.com/doc/inun.asp
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