Guest Lecture: Liang Peng

Systemic Risk – CoVaR, Comovement and Portfolio Selection

Dr. Peng has been the Thomas P Bowles chair professor of actuarial science in the Maurice R. Greenberg School of Risk Science in the Robinson College of Business at Georgia State University since August 2014. He was a faculty member in the School of Mathematics at Georgia Institute of Technology from January 2001 to August 2014. Dr. Peng has published one book on heavy-tailed data analysis and more than 180 papers in various statistics, econometrics, and actuarial science journals. His research interests include Extreme Value Analysis, Econometrics, Risk Analytics, Actuarial Science, and Mutual Fund Management.Dr. Peng received his Ph.D. in 1998 from Erasmus University Rotterdam in the Netherlands and became an elected fellow of the Institute of Mathematical Statistics in 2009 and the American Statistical Association in 2012. His editorial board services include an associate editor for the Journal of American Statistical Association (2017--2023),  Statistica Sinica (2011--2020),  Annals of Statistics (2007--2009), Extremes (2007 --2014), Scandinavian Journal of Statistics (2014--2020),  Statistics and Probability Letters (2012--2013), Statistics and Its Interface (2010--2013), Journal of Korean Statistical Society (2008--2013), ASTIN Bulletin (2021 --2026), and Variance (2025-2027). He is currently Fellow-in-residence at CYAS, invited by the ESSEC Business School.

Systemic risk concerns the impact of an individual entity on a financial system, while (extreme) comovement measures one individual (extreme) loss given another individual (extreme) loss. A natural and challenging question is how to measure and forecast the collective impact of two individual losses on systemic risk, conditional on certain predictors and the comovement of these two individuals. In this paper, we introduce a novel systemic risk measure, CoVaRCM, which integrates both comovement and predictor variables to assess the joint effect of two individual losses on systemic risk. Since the comovement event in our model depends on predictors and has zero probability,  we employ a three-quantile regression model to conduct an efficient inference. We further propose two metrics to compare CoVaRCM with the more conventional CoVaR. Our empirical analysis demonstrates the significant influence of comovement on systemic risk. We also discuss a statistical inference for systemic risk-driven portofolio selection.


Date: June 24th, 2025 from 2pm to 3pm.
The hybrid guest lecture is organised in person at the H008 meeting room of MIR in Neuville-sur-Oise and remotely on Zoom.

To attend the remote guest lecture, please connect to Zoom: https://cyu-fr.zoom.us/j/99072338379


The video will be online on the CY AS YouTube channel