The Chair “Stress Testing” is a specific research program, hosted by the Center of Applied Mathematics between 

This research project is part of an in-depth reflection on the increasingly sophisticated issues surrounding stress tests (under the impulse of the upcoming European Banking regulation). Simulation of extreme adverse scenarios is an important topic to better understand which critical configurations can lead to financial and systemic crises. These scenarios may depend on complex phenomena, for which we partially lack information, making the modeling incomplete and uncertain. Last, the data are multivariate and reflects the dependency between driving variables.

Lines of research:

Keywords: Bayesian Networks, climate finance, copulas, credit risk, cyber risk, dependent data, Deep Learning, Gaussian processes, machine learning, Markov Chain Monte Carlo, meta-modeling, multivariate statistics, rare event simulation, risk metrics, splitting methods, stochastic algorithms, stochastic and Bayesian optimization, uncertainty propagation, uncertainty quantification

CAPSULES

Teacher portrait - Emmanuel Gobet Neural Network generative model of Fractional Brownian motion
2023, May : Video teaser by Michael Allouche on "EV-GAN : Simulation of extreme events with ReLU neural networks" during ICLR 2023. The work has been published in Journal of Machine Learning Research.