Financial Mathematics, Operational Research and Statistics Group
Finance, Operational Research and Statistics (FORS) group encompasses applied and theoretical research within three inter-related broad areas of research: financial mathematics, operational research and applied statistics.
The list below highlights a number of the research activities being undertaken, and lists the names of the various members of the group who are active in these areas. For more detailed descriptions of our research as well as other relevant information (collaborations, lists of publications, projects, conference presentations, and so on) please follow the links to the web pages of individual group members.
Research interests and activities
- Information-based asset pricing with applications to equities, credit, and commodities (Brody, Hughston, Meier)
- Social discounting, and the valuation of very long term projects (Brody, Hughston, Meier)
- Models of interest rates, foreign exchange, and inflation (Brody, Hughston, Meier)
- Nonlinear filtering and its applications in financial time series models (Date)
- High-dimensional multivariate statistical modelling, with applications on gene expression data (Lewin, Liverani, Vinciotti, Yu)
- Modelling of discrete data, with applications on reliability and deep-sequencing data (Vinciotti, Yu)
- Quantile regression and its applications in energy and environment (Liverani, Vinciotti, Yu)
- Applied Bayesian statistical inference (Lewin, Liverani, Vinciotti, Yu)
- Lifetime data analysis with application in engineering and health (Yu)
- Sampling from partially specified multivariate distributions, i.e. scenario generation (Date, Roman)
- Risk measurement and optimization of financial portfolios (Date, Lucas, Roman, Yu)
- Metaheuristic methods in combinatorial optimization (Beasley, Lucas, Mladenovic)