The members of the Discipline of Business Analytics (BA) have a range of research interests across the fields of Analytics: including Statistics, Econometrics, Financial Econometrics, Financial time series, Operations Research, Operations Management and Machine Learning. Staff members in BA regularly publish in leading international journals in these fields. The quantitative skills of the group are applied to business problems in the Operations, Finance and Marketing areas, as well as issues arising in Economics.
This research requires a rigorous approach to model formulation and estimation as well as the skills to analyse the outputs of these models. The BA group has the ability to carry out strategic and well-focused analyses of real-world problems across discipline boundaries.
There are particular research strengths in:
- Big Data analytics (Junbin Gao, Sally Wood, Richard Gerlach, Artem Prokhorov, Marcel Scharth, Minh-Ngoc Tran)
- Applied econometrics (Andrey Vasnev, Laurent Pauwels, Richard Gerlach, Marcel Scharth)
- Electricity markets (Eddie Anderson)
- Financial econometrics and Quantitative risk forecasting (Artem Prokhorov, Richard Gerlach, Boris Choy, Marcel Scharth)
- Bayesian methods (Richard Gerlach, Boris Choy, Sally Wood, Junbin Gao, Marcel Scharth, Minh-Ngoc Tran)
- Forecasting, Sensitivity Analysis (Andrey Vasnev, Richard Gerlach)
- Micro-econometrics, Multivariate statistical methods (Artem Prokhorov, Marcel Scharth)
- Panel data methods and models (Artem Prokhorov, Laurent Pauwels, Minh-Ngoc Tran)
- Scheduling problems (Daniel Oron)
- Stochastic non-life insurance and actuarial problems (Boris Choy)
- Supply Chains (Eddie Anderson, Erick Li, Dmytro Matsypura)
- Testing and modelling structural change (Laurent Pauwels, Richard Gerlach, Sally Wood)
- Time Series and forecasting (Richard Gerlach, Boris Choy)
- Statistical Machine Learning (Junbin Gao, Minh-Ngoc Tran, Artem Prokhorov).
The BA group welcomes approaches from potential PhD students with an interest in one of these areas.