He completed his undergraduate studies in economics (Supra Cum Laude) at the Vrije Universiteit Brussel in 1979.

[5] After graduation from the Kellogg School of Management at Northwestern University he took a faculty position at the Université de Montréal in the Department of Economics.

Since 2018 he is the Faculty Research Director, Rethinc.Labs, at the Kenan Institute for Private Enterprise at UNC Chapel Hill.

[8] Ghysels is a fellow of the American Statistical Association and co-founded with Robert Engle the Society for Financial Econometrics (SoFiE).

[14] In 2018, he published a textbook entitled Applied Economic Forecasting using Time Series Methods together with Massimiliano Marcellino.

[15] His honors and awards include: Ghysels' most recent research focuses on Mixed data sampling (MIDAS) regression models and filtering methods with applications in finance and other fields.

It incorporates each individual high-frequency data in the regression, which solves the problems of losing potentially useful information and including mis-specification.

The regression models can be viewed in some cases as substitutes for the Kalman filter when applied in the context of mixed frequency data.

Bai, Ghysels and Wright (2013)[29] examine the relationship between MIDAS regressions and Kalman filter state space models applied to mixed frequency data.

High-dimensional mixed frequency time series regressions involve certain data structures that once taken into account should improve the performance of unrestricted estimators in small samples.

To that end, the machine learning MIDAS approach exploits the sparse-group LASSO (sg-LASSO) regularization that accommodates conveniently such structures.