Stéphane Crépey graduated from ENSAE ParisTech and holds a PhD in differential games and mathematical finance from Ecole Polytechnique and INRIA Sophia Antipolis. He is Distinguished Professor of Mathematics at the Université de Paris, Laboratoire de Probabilités, Statistique et Modélisation (LPSM), Team Mathematical Finance and Numerical Probability (MathFiProNum).
Stephane’s research interests are financial modeling; counterparty credit risk, XVA analysis, risk measures; risk management for central counterparties; simulation, calibration, training, and machine learning techniques; uncertainty quantification, model risk; and the related mathematical topics in the fields of backward stochastic differential equations, random times modeling, enlargement of filtration, and numerical probability. He is the author of numerous research papers and two books: “Financial Modeling: A Backward Stochastic Differential Equations Perspective” (S. Crépey, Springer Finance Textbook Series, 2013) and “Counterparty Risk and Funding, a Tale of Two Puzzles” (S. Crépey, T. Bielecki and D. Brigo, Chapman & Hall/CRC Financial Mathematics Series, 2014). He is an associate editor of SIAM Journal on Financial Mathematics, Journal of Computational Finance, International Journal of Theoretical and Applied Finance, Journal of Dynamics and Games, and a member of the scientific council of the French financial markets authority (AMF).
Gaussian process regression for derivative portfolio modeling and application to credit valuation adjustment computations
The authors present a multi-Gaussian process regression approach, which is well suited for the over-the-counter derivative portfolio valuation involved in credit valuation adjustment (CVA) computation.