The Essex Centre for Macro and Financial Econometrics (ECMFE) warmly invite you to join guest speaker Professor Zudi Lu as they discuss their work on Dynamic Time Series Forecasting.
14:00 - 16:00
Professor Zudi Lu, University of Southampton
Lectures, talks and seminars
Essex Centre for Macro and Financial Econometrics (ECMFE) Research Seminar Series
Essex Business School
Professor Robert Taylor email@example.com
The Essex Centre for Macro and Financial Econometrics brings together academic and industry expertise from inside and outside the University of Essex to research and help solve important issues in financial markets.
Forecasting is the process of making predictions of the future based on past and present data. In the modern data science age, a large amount of data is easily available.
How to deal with high-dimensional modelling is no doubt a common challenge, in particular for time series dynamic forecasting.
Partial information based modelling and combination methods provide a useful way to handle a large number of variables (including dynamic lag variables), in particular when delving into nonlinear extraction of information from a large number of variables for forecasting.
In this talk, Professor Lu will review some of the ideas and progresses that my collaborators that he has developed with semiparametric model averaging for dynamic time series forecasting, and present some of our recent developments in methodology and applications in economic and financial modelling.
This seminar is free to attend however entry is password protected. Please contact the organisers for the password.
Professor Zudi Lu is Professor/Chair in Statistics in Mathematical Sciences and Southampton Statistical Sciences Research Institute (S3RI) at University of Southampton, UK.
Prior to that, he had worked at several international academic institutions, including
after he received his PhD degree from the Chinese Academy of Sciences in 1996.
He was a recipient of the Australian Research Council Future Fellowship in its 2010 round and other national/international grants from China, Australia and Europe, and is an elected member of the International Statistical Institute.
His current research interests range from nonlinear time series to nonlinear spatial and spatiotemporal data modelling and machine learning with applications to economic, financial and environmental modelling etc..