Professor Ghysels is a fellow ot the American Statistical Association and co-founded with Robert Engle the Society for Financial Econometrics (SoFIE). He is also-coeditor of the Journal of Financial Econometrics.

In 2008-2009, Ghysels was resident scholar at the Federal Reserve Bank of New York, and has since been a regular visitor of the bank as well as several other central bank institutions around the world working mostly on topics pertaining to Mixed data sampling regression models and filtering methods.

In this Lecture Series, Professor Ghysels will present his most recent research that focuses on Mixed data sampling (MIDAS) regression models and filtering methods with applications in finance and other fields. MIDAS regressions are econometric regression models and can be viewed in some cases as substitutes for the Kalman filter when applied in the context of mixed frequency data.

"Big" is in parenthesis in the title because the lecture series will start with MIDAS applications for conventional data sets and then more toward big mixed frequency big data analysis.

Program (3 hours every morning)

Monday September 9, 2019
10:00 - 13.00 : Midas regression: introduction
13:00 : Welcome Lunch

Tuesday, September 10, 2019
09:00 - 12.00 : Multivariate models

Wednesday, September 11, 2019
09:00 - 12.00 : Practical session

Thrusday, September 12, 2019
09:00 - 12.00 : Volatility, correlation and skewness

Friday, September 12, 2019
09:00 - 12.00 : Mixed frequency big data

Practical information

Participation is free but MANDATORY (in case of registration and no-show, we will charge you 100€)

A welcome lunch on September 9, and coffee breaks in the morning will be provided.

To register fill in the online form by August 31, 2019.