Eric Ghysels
Edward Bernstein Distinguished Professor of Economics and Professor of Finance, Faculty Director of Rethinc. Labs
Eric Ghysels is the Edward Bernstein Distinguished Professor of Economics and a finance professor at UNC Kenan-Flagler.
His main research interests are time series econometrics and finance.
He teaches empirical finance and time series PhD courses. He has published in the leading economics, finance and statistics journals. He served on the editorial boards of several academic journals and is co-editor of the Journal of Business and Economic Statistics.
Dr. Ghysels, who speaks French, Dutch and German, has been a visiting professor or scholar at several major U.S., European and Asian universities.
He is an amateur piano player.
He received his PhD and MA from Northwestern University and his BA from the University of Brussels.
Recent Publications
May 7, 2024
We formulate quantum computing solutions to a large class of dynamic nonlinear asset pricing models using algorithms, in theory exponentially more efficient than classical ones, which leverage the quantum properties of superposition and entanglement. The equilibrium asset pricing solution is a quantum state. We introduce quantum decision-theoretic foundations of ambiguity and model/parameter uncertainty to deal with model selection.
March 22, 2021
A term originated in meteorology, nowcasting pertains to the prediction of the present and very near future. Nowcasting applications in economics and finance are intrinsically a mixed frequency data problem as the object of interest is a low-frequency data series (e.g., quarterly), whereas the information is real-time high frequency (e.g., daily, weekly, or monthly).
December 10, 2020
The cryptocurrency industry has evolved significantly over the last five years. It is no longer purely speculative; use cases that add real value are emerging, and with them, significant institutional interest. Rethinc. Fintech Labs Faculty Director and Professor of Finance Eric Ghysels recently sat down with Zoe Cruz, former co-president of Morgan Stanley, to discuss the impact of adding cryptocurrencies to a traditional portfolio.
November 7, 2020
The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance swaps. Standard machine learning methods tend to identify contracts which are illiquid, and hard to trade.
October 16, 2020
The importance of asymmetries in prediction problems arising in economics has been recognized for a long time. In this paper, we focus on binary choice problems in a data-rich environment with general loss functions.
May 28, 2020
Traditional contact tracing, where workers query patients about their interactions to see who else might have been infected — and perhaps to find out where they got the infection — is being widely used. But for the first time, many public health authorities are considering, or have implemented, smart phone apps to partially automate and scale contact tracing.