Publications

2025

  • Barrera, S. Crépey, E. Gobet, H.-D. Nguyen, and B. Saadeddine. Statistical learning of the value-at- risk and expected shortfall. Forthcoming in Mathematical Finance.
  • Abbas-Turki, B. Li, S. Crépey, and B. Saadeddine: An explicit scheme for pathwise XVA computations. Journal of Computational Finance 28(4), 1–36, 2025.
  • A. Alouadi, B. Barreau, L. Carlier, H. Pham: Robust time series generation via Schrödinger bridge: a comprehensive evaluation, arXiv:2503.02943
  • F. Baschetti, G. Gazzani, J. Guyon, Affine and polynomial path-dependent volatility models, in preparation.
  • F. Bourgey, J. Guyon, Fast Smile Calibration in Discrete and Continuous Time, in preparation.
  • A. De Crescenzo, F. De Feo, H. Pham: Linear-quadratic optimal control for non-exchangeable mean field SDEs and applications to systemic risk, arXiv:2503.03318
  • J. Delemotte, S. De Marco, J. Guyon: Bergomi models with volatility memory, in preparation.
  • G. Gazzani, J. Guyon: Pricing and Calibration in the 4-Factor Path-Dependent Volatility Model, Quantitative Finance 25(3):471–489, 2025.
  • J. Guyon: Dispersion-Constrained Martingale Schrödinger Bridges: Joint Entropic Calibration of Stochastic Volatility Models to S&P 500 and VIX Smiles, forthcoming in SIAM Journal on Financial Mathematics, 2025.
  • J. Guyon, T. Jeannin, B. Jourdain: On the surjectivity of the conditional expectation given a real random variable, in preparation.
  • J. Guyon, T. Jeannin, B. Jourdain: Smile expansions in path-dependent volatility models, in preparation.
  • J. Guyon, L. Parent: The Discrete-Time 4-Factor Path-Dependent Volatility Model: Calibration under P and Q, in preparation.
  • I. Kharroubi, S. Mekkaoui: Stochastic maximum principle for optimal control of non exchangeable mean field system, arXiv:2506.05595
  • P. Henry-Labordère, G. Loeper, O. Mazhar,  H. Pham: Generative diffusion models : bridging Schrödinger and Bass, work in progress.
  • O. Mazhar, H. Pham : Non-parametric Estimation of the Drift of a Time Series Schrödinger bridge, work in progress.
  • H. Pham, X. Warin: Actor critic learning algorithms for mean field control with moment neural networks, Methodology and Computing in Applied Probability, 27(3), 2025. 
  • Denkert R., H. Pham, X. Warin : Control randomisation approach for policy gradient and application to reinforcement learning in optimal switching,  Applied Mathematics and Optimization, 2025, vol 91(9).

2024

  • Abi Jaber E., De Carvalho N., H. Pham : Trading with propagators and constraints : applications to optimal execution and optimal storage, arXiv :2409.12098
  • R. Denkert, I. Kharroubi, H. Pham: A randomisation method for mean-field control problem with common noise, arXiv:2412.20782, in revision for Electronic Journal of Probability.
  • Benezet C., and S. Crépey. Handling model risk with XVAs. Frontiers of Mathematical Finance 3(4), 490-519, 2024.
  • F. Bourgey, J. Guyon, Fast exact joint S&P 500/VIX smile calibration in discrete and continuous time, Risk, February 2024. [SSRN preprint 4315084]
  • B. Li, S. Crépey, H. D. Nguyen, and B. Saadeddine. CVA sensitivities, hedging, and risk.  Risk Magazine July 2024.
  • S. Crépey, Invariance times transfer properties. Probability, Uncertainty and Quantitative Risk 9(4), 431-452, 2024.
  • Chassagneux, J.F., G. Pagès Computing the invariant distribution of McKean-Vlasov SDEs by ergodic simulation, arXiv : 2406.13370
  • Coculescu D., Motte M., H. Pham : Opinion dynamics in communities with major influencers and implicit social influence via mean-field approximation, Mathematical and Financial Economics, 2024, vol. 18, 333-377.
  • Coppini F., De Crescenzo A., H. Pham : Nonlinear graphon mean-field systems, arXiv : 2402.08628,  forthcoming in Stochastic Processes and their Applications
  • S. Crépey, N. Frikha, and A. Louzi. A multilevel stochastic approximation algorithm for unbiased value-at-risk and expected shortfall estimation. Forthcoming in Finance and Stochastics.
  • S. Crépey, N. Frikha, A. Louzi, and G. Pagès. Asymptotic error analysis of multilevel stochastic approximations for the value-at-risk and expected shortfall. Electronic Journal of Probability 29 (198) 1-56, 2024.
  • De Crescenzo A., Fuhrman M., Kharroubi I., H. Pham : Mean field control of non exchangeable systems, arXiv : 2407.18635
  • Frikha N., Germain M., Laurière M., H. Pham, X. Song : Actor-critic learning for mean-field control in continuous time, forthcoming in Journal of Machine Learning Research.
  • Frikha N., H. Pham, Song X. : Full error analysis of policy gradient learning algorithms for exploratory linear quadratic mean field control problem in continuous time with common noise, arXiv : 2408.02489, in revision for Journal of Machine Learning Research.
  • J. Guyon, Dispersion-Constrained Martingale Schrödinger Problems and the Exact Joint S&P 500/VIX Smile Calibration Puzzle, Finance and Stochastics, 28(1):27-79, 2024.

2023

  • J. Guyon, J. Lekeufack: Volatility is (mostly) path dependent, Quantitative Finance 23(9):1221–1258, 2023 [SSRN preprint 4174589]
  • L. Abbas-Turki, S. Crépey, and B. Saadeddine. Pathwise CVA regressions with oversimulated Defaults. Mathematical Finance, 33(2), pages 274-307, 2023.
  • J. Guyon, S. Mustapha: Neural joint S&P 500/VIX smile calibration, Risk, December 2023. [SSRN preprint 4309576]
  • M. El Amrani, J. Guyon : Does the term-structure of the at-the-money skew really follow a power law? Risk, August 2023 [SSRN preprint 4174538]
  • M. Hamdouche, P. Henry Labordère, H. Pham: Generative modeling for time series via Schrödinger bridge, [arXiv:2304.05093], in revision for Journal of Machine Learning Research.
  • M. Hamdouche, P. Henry Labordère, H. Pham: Policy gradient learning methods for stochastic control with exit time and applications to share repurchase pricing, [arXiv:2302.07320], Applied Mathematical Finance, 29(6), pp.  439-456, 2023.
  • W. Lefebvre, G. Loeper, H. Pham: Differential learning methods for solving fully nonlinear PDEs, Digital Finance, vol 5, 183-229
  • M. Germain, H. Pham, X. Warin: Neural networks-based algorithms for stochastic control and PDEs in finance, Machine Learning and Data Sciences for Financial Markets: a guide to contemporary practices, Cambridge University Press, Editors: Agostino Capponi and Charles-Albert Lehalle