Jiali XU is a Quantitative analyst of Operational Risk Modeling at Société Générale. After graduating from the Ecole des Ponts Paristech (ENPC) in 2014, Jiali joined Société Générale in 2014 and serves as a quantitative analyst supporting Operational Risk Modeling. His current research projects are in the areas of applications of random matrix theory in risk measurement.
This paper uses simulation studies and an example of operational risk modeling to show the necessity and benefit of using RMT to fit high-dimensional t-copulas in risk modeling.
This paper focuses on the distribution of correlations among aggregate operational risk losses.