Joint Seminar with Economics Department - Filtering and Classical Estimation for Continuous Time Finance Models

He obtained a D.Phil at Nuffield College, Oxford under the supervision of Neil Shephard and following this held a post-doc position in the department of mathematics, Imperial College, London. Currently he works on computationally intensive methods for statistics and econometrics, in particular for time series models. He has developed efficient Bayesian methods for analysing discrete time stochastic volatility models which arise in finance, relying on Monte Carlo methods. In addition, his research has focused on efficient methods for filtering time series models. This has become an important issue in finance where the interest in conditioning upon information as it arises. Recently he has been concerned with the estimation and filtering for stochastic differential equations which categorise continuous time models.