The Chair “Stress Testing” is a specific research program, hosted by the Center of Applied Mathematics between 
  • Ecole Polytechnique
  • BNP Paribas
  • Fondation de l'Ecole Polytechnique
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:
  1. Generation of stress test and meta-modeling scenarios using machine learning
  2. Quantification of uncertainties in risk metrics
  3. Modeling and estimation of multidimensional dependencies


Keywords: Bayesian Networks, copulas, 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, climate-change, carbon taxation.