Supervisor: Dr Alexander Shestopaloff
Project description:
This project will focus on the development of novel statistical methodology for the forecasting of high-dimensional time series, with an application to financial data sets. Of particular interest is the forecasting of time series with sparse temporal observations, including missing data, yet having a high cross-sectional dimension. This presents challenges in practice and requires the development of new methods that are able to take this into account in a theoretically justified way. The student will have the opportunity to develop statistical methodology and apply it to real-world scenarios including rigorously testing it on current data.
Further information: How to apply Entry requirements Fees and funding