Our research focuses on the use of high performance systems, the analysis of massive data sets, and efficient algorithms for financial computing.

Financial computing is computationally intensive, and so for many applications parallelization is a necessity. One ongoing project is the development of a highly efficient parallelizable database with a rich query language usable, which will allow the testing of, for example, asset pricing models, algorithmic trading strategies, and market impact models, directly within the database.

Another focus of our research is the application of statistical learning to computational finance problems.

Our research benefits from the parallel computing facilities offered by the Centre for Scientific Computing and from the cooperation with the Department of Computer Science, the Warwick Mathematics Institute, the Warwick Business School, and the Department of Psychology.