Economics, Finance and Business
This theme is concerned with the application of statistical, econometric and machine learning methods to problems arising in economics, finance and business.
Theme Overview
This theme is concerned with the application of statistical, econometric and machine learning methods to problems arising in economics, finance and business.
Theme Members
- Niloufar Abourashchi
- Gianluca Baio
- Alex Beskos
- Petros Dellaportas
- Jim Griffin (Theme Lead)
- Nuru Giritli
- Serge Guillas
- Sebastian Maier
- Ioanna Manolopoulou
- Giampiero Marra
Current and Recent Externally Funded Projects
- Bayesian computations for Value of Information measures using Gaussian processes, INLA and Moment Matching, PI: Baio
- Bayesian non-parametric modelling to understand product competition, PI: Manolopoulou
- Detecting Anomalies in Networks: The Case of VAT (Turing HSBC Economic Data Science Project), PI: Dellaportas
- Forecasting with Large Macroeconomic and Financial datasets in the Presence of Structural change (Turing HSBC Economic Data Science Project, PI: Dellaportas
- Hawkes processes to model slow-moving goods, PI: Manolopoulou
- Health economic evaluation of HPV vaccination, PI: Baio
- The regression discontinuity design in epidemiology, PI: Baio
- Topic models for market baskets, PI: Manolopoulou