Mathematical finance; nonlinear filtering, power systems optimization.
- Algorithms for latent state estimation or ‘filtering’ in nonlinear time series and applications of filtering, especially for forecasting and risk measurement in mathematical finance.
- Use of artificial neural networks in financial modelling and asset price prediction.
- Optimization problems in power systems.
I have supervised 11 PhD students and 3 MPhil students to successful completion. Recently finishing students are
- Dr Zryan Sadik, Asset price and volatiltiy forecasting using news sentiment (2018).
- Dr Seham Allahyani, Contributions to filtering under randomly delayed observations and additive-multiplicative noise (2018).
- Dr Suren Islyaev, Stochastic models with random parameters in finance (2015).
Research project(s) and grant(s)
2013: Variable sampling rate filtering for nonlinear time series, EPSRC overseas travel grant ( EP/L019477/1), £8775.