Parallel Computing with MATLAB in Computational Finance

Yi Wang, MathWorks

Financial organizations are concerned increasingly with the need for more comprehensive analysis and working with larger data-sets. MathWorks parallel computing products – Parallel Computing Toolbox and the MATLAB Distributed Computing Server – provide an easy-to-use environment for speeding up and increasing the scope of your MATLAB applications using high-performance resources including multicore desktops, clusters/grids and GPUs.

In this webinar we introduce how you can use these products for applications in computational finance such as portfolio optimization, backtesting, risk analysis, option pricing, and model calibration.

Webinar highlights include:

  • An introduction to parallel computing with MATLAB
  • A summary of the many parallelizing options available to you with the MATLAB Parallel Computing Toolbox and MATLAB Distributed Computing Server.
  • A number of computational finance examples, all running extremely fast
  • Integrating parallel MATLAB applications into production environments, using the MATLAB Compiler and the Application Deployment Target products.

About the Presenter: Yi Wang joined MathWorks in September 2007 as an Applications Engineer working on the Computational Finance Team. He holds a B.ASc. in Computer Engineering from the University of Toronto and an M.S. in Computer Engineering from the University of Illinois at Chicago and a second M.S. in Computer Science from the University of Southern California. Before joining MathWorks, Yi worked at Motorola in Illinois for seven years, as a software engineer developing wireless communications infrastructure and later as a patent portfolio analyst managing Motorola’s intellectual property processes. 

Die Arbeitsweise der folgenden Werkzeuge wird gezeigt

  • Parallel Computing Toolbox
  • Financial Toolbox
  • MATLAB Distributed Computing Server

Aufgezeichnet: 5 Okt 2010