Introduction to statistical finance with R

During the first part of our meeting, Nicolas Christou gave an introduction of statistical finance in R, and presented a package he co-authored with previous PhD student David Diez (2010). Video of the talk is below:

During the second part, we accommodated shorter talks outlining R users’ experiences with statistical finance in R.

Kyle Matoba, a Finance PhD student from UCLA Anderson School of Management, presented on Algorithmic Trading with R.

Bryce Little, UCLA alum, presented on Constructing Minimum Variance Portfolios with R.

How to build a world-beating predictive model using R

Many modern data analysis problems in both industry and academia involve building a model that can predict the future based on historical variables. The 2009 KDD Cup was an international data mining competition devoted to this type of problem, where contestants attempted to predict the behaviour of mobile phone customers using an extensive database of historical information. The University of Melbourne team managed to win one part of this challenge, using R almost exclusively. In this talk I’ll give some background to the area and the specific problem, and discuss how we went about building our models. The talk will be fairly accessible, and deal with many of the practical issues encountered in this type of work.


SURF Meet Up Group