During recent years, the use of intelligent systems in the financial and economic industries have increased substantially, providing a new perspective to the agenda of finance and economics by their ability to handle large amounts of financial data and simulate complex models. This field of research is known as computational finance. The most common applications of computational finance are within the area of investment banking and financial risk management, and currently employ learning methods such as Support Vector Machines, Bayesian approaches, Regression, Neural Network, Fuzzy Logic and Genetic Algorithms.

The aim of the workshop is to open discussion and stimulate interaction between the disciplines of computational finance and machine learning geared towards the development of new methods that will answer specific complex questions in finance. The workshop is targeted towards academics and professionals alike.

The workshop is organised by the centre for Computational Statistical and Machine Learning (CSML) and by the Financial Computing Team at University College London under the sponsorship of the Patterns Analysis, Statistical Modelling and Computational Learning (PASCAL) Network of Excellence 2.

Detailed information can be found at the Workshop homepage.