Wolfram Computation Meets Knowledge

Date Archive: 2011 February

Education & Academic

Optimizing Financial Modeling with Mathematica

On January 25 and 27 in Chicago and New York, respectively, Wolfram, in conjunction with NVIDIA, hosted a seminar themed "Optimizing Financial Modeling" to showcase how Mathematica and CUDA can be applied within the financial industry. Full presentations and a white paper on CUDA programming with Mathematica are available for download on the seminar page. Dr. Phillip Zecher, Chief Risk Officer of EQA Partners, detailed how Mathematica is used in every facet of his firm's operation, and NVIDIA's Senior CUDA Consultant John Ashley explained how CUDA programming is changing financial computation. My talk concerned Mathematica 8's broad functionality for finance. Each capability is deserving of a full seminar unto itself, so because of the sheer number of topics and functions, I was only able to briefly touch on a few examples from each category. A full list of financial tools in Mathematica is available in the online documentation. The following TabView presents an overview of the new financial functions:
Education & Academic

An Educator’s Story: Creating Immersive Teaching Environments with Mathematica

Paul Abbott, a faculty member in the School of Physics at The University of Western Australia, wants to teach his students a tool that they can use to tackle real-world problems—not only in his physics and mathematics courses, but throughout their studies and into their professional careers. For him, Mathematica is that tool. Abbott uses Mathematica to build all of his courseware, from lecture slide shows and assignments to quizzes and exams. His students use Mathematica to visualize surfaces, explore concepts using interactive examples, hypothesize results, and check their work. He says Mathematica is an "immersive environment" that helps his students reach a higher level of understanding.
Design & Visualization

Retreat from Blenheim

When last seen in the whereabouts of the Marlborough Maze, I was slinking off stage left, having been upstaged by Jon McCloone and his mix of image processing and graph theory alchemy. In a comment on my post, Jaebum Jung showed similar methods. Me, I only wanted to compute a bunch of distances from the entrance, then walk the maze. But I was not at that time able to show which was the shortest path, or even to prune off the dead ends. I'm over that lapse now. In this post I will provide brief Mathematica code to take the grid of maze pathway distances that I computed, and get the hopeless paths to melt away. Technically this is referred to as a retraction—not in the sense of an apology, but, rather, topology.