Eric Ghysels

Who is Eric Ghysels?

Eric Ghysels is the Bernstein Distinguished Professor of Economics at the University of North Carolina - Chapel Hill and Professor of Finance at the Kenan-Flagler Business School. His main research interests are time series econometrics and finance. He obtained his Ph.D. from the Kellogg Graduate School of Management at Northwestern University. He has been a visiting professor or scholar at several major U.S., European and Asian universities. He serves on the editorial boards of several academic journals and was co-editor of the Journal of Business and Economic Statistics and editor of the Journal of Financial Econometrics. He has published in the leading economics, finance and statistics journals and has published several books. He is also the Founding Co-President of the Society for Financial Econometrics (SoFiE). He was a Resident Scholar at the Federal Reserve Bank of New York during 2008-2009 and a Duisenberg Fellow at the European Central Bank in 2011.

For further information, visit Eric Ghysels's personal website.

How will Eric Ghysels cooperate with Louvain Finance?

Prof. Ghysels will cooperate with the finance team along several research lines:

  • Quantile MIDAS regression: Using quantile MIDAS regression, the project analyzes the predictability of inflation rate distribution as a function of daily, weekly and monthly state variables. The use of MIDAS regression allows us to include higher frequency information in our predictors' set in a parsimonious way. In addition, by using quantile regression model we can explore certain parts of the distribution and thereby characterize the downside risks of inflation rate. The methodology is applied to Euro area inflation rate.
  • LASSO MIDAS. This study extends MIDAS modelling framework in a high dimensional setting by augmenting the regression model with Ridge and Lasso type of penalties. To increase computational efficiency, the likelihood profiling approach is used in parallel with coordinate descent to estimate high dimensional MIDAS model. The method is applied to forecast (now-cast) Euro area MIR rates.
  • Alternative investments. Initially this research line will focus on the art market by constructing high frequency art indices, including sub-indices for American, Old Master, Impressionist and Modern paintings for various time periods.
  • Non-Gaussian Term Structure Models. Ongoing projects (i) document the role that conditional asymmetry in the term structure of government bonds plays in bond expected returns, (ii) analyze the macro-financial drivers of bond yield conditional skewness, and (iii) build arbitrage-free non-Gaussian term structure models featuring conditional asymmetry in their risk factors which are consistent with empirical patterns documented.
  • Investor Behaviors in Turbolence Times: The research project aims at a better understanding of investors’ behaviors during the financial crisis. More specifically, the analysis is focused on investors’ trades in bank stocks when the prices were under big pressure (September 2008 – April 2009).  Using a unique database from an important Belgian online brokerage house, we investigate the behavior of more than 50,000 retail investors regarding stocks within the bank sector. Our database includes usual information relative to investors' orders and trades but also their answers to the MiFID questionnaires (including information about their risk aversion, their investment targets and their wealth level).