2020 SoFiE Summer School in Chicago: Econometrics of Mixed Frequency (Big) Data

The Stevanovich Center for Financial Mathematics is pleased to host the 2020 SoFIE Summer School
from Monday, July 20 to Friday, July 24, 2020
on The Econometrics of Mixed Frequency (Big) Data

Thank you to all who attended this special Summer School, and to our wonderful instructors! Please sign up to receive announcements re. future events.

Description:

  • Professors Babii and Ghysels will present research that focuses on MIxed Data Sampling (MIDAS) regression models and filtering methods with applications in finance and other fields. MIDAS regressions 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 for conventional data sets and then cover mixed frequency data analysis using machine learning and other large dimensional data econometric techniques.
  • This Summer School is intended for students, researchers and professionals in statistics, econometrics and finance. It assumes familiarity with basic regression analysis, principles of univariate and multivariate time series analysis as well as basic models of volatility but is otherwise self-contained. Students will be provided with a packet of lecture notes when the course starts.
  • The course will offer to a limited and selected number of course participants an opportunity to present their current research.
  • Take a look at our program overview! Details will be added as they become available.

 

Lecturers:

  • Professor Andrii Babii, University of North Carolina at Chapel Hill
    Andrii Babii is an Assistant Professor of Economics at the University of North Carolina at Chapel Hill. He obtained his Ph.D. from the Toulouse School of Economics in France. He has published in leading econometrics journals. His most recent research focuses on machine learning and big data analysis in econometrics, causal inferences, nonparametric and high-dimensional statistics. He was a recipient of several scholarships and awards, including the Jean-Jacques Laffont Scholarship and the Jae-Yeong Song and Chunuk Park Teaching Award. He is also the alumni of the 2013 SoFiE Summer School at Oxford University and the 2014 SoFiE Summer School at Harvard University.
  • Professor Eric Ghysels, University of North Carolina at Chapel Hill
    Eric Ghysels is the Edward M. Bernstein Distinguished Professor of Economics at the University of North Carolina at Chapel Hill and Professor of Finance at the Kenan-Flagler Business School. 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 served 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 the 2008-2009 financial crisis and a Duisenberg Fellow at the European Central Bank in 2011 during the sovereign debt crisis. He is a Fellow of the American Statistical Association, Fellow of the Journal of Econometrics, Fellow of the Society for Financial Econometrics and holds a Honorary Doctorate from HEC Liege. He is currently co-editor of the Journal of Applied Econometrics and Faculty Research Director of the Rethinc.Labs at the Kenan Institute. His most recent research focuses on MIDAS (meaning Mi(xed) Da(ta) S(ampling)) regression models and related econometric methods, machine learning, artificial intelligence, big data, FinTech, and quantum computing applications in finance.

 

Useful Links:

 

Timeline:

  • The application deadline is May 10, 2020. Please email sbendier@uchicago.edu if you’re interested in attending the Summer School.
  • Your application should include a full CV and a brief motivation letter (200 words maximum) explaining why attending this course would be helpful to your research or career
  • Applicants are strongly encouraged to present some of their own work during the afternoon sessions. If you’d like to present during the summer school, please submit a paper or a long abstract along with your application
  • Decisions will be emailed by May 22 at the latest. If you are accepted, your deadline to register will be June 30, 2020. Your registration will be confirmed at the time your payment is submitted.
  • May 22-June 30: Registration period
  • July 20-24, 2020: Summer School (will be held online this year.)