2024
- Abi Jaber E., De Carvalho N. et H. Pham : “Trading with propagators and constraints : applications to optimal execution and optimal storage”, arXiv :2409.12098
- Benezet C., and S. Crépey. Handling model risk with XVAs. Forthcoming in Frontiers of Mathematical Finance(doi:10.3934/fmf.2024016, 30 pages).
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Chassagneux, J.F. et G. Pagès Computing the invariant distribution of McKean-Vlasov SDEs by ergodic simulationarXiv : 2406.13370
- Coculescu D., Motte M. et 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., et H. Pham : “Nonlinear graphon mean-field systems”, arXiv : 2402.08628, en révision à Stochastic Processes and their Applications
- Crépey S., N. Frikha, and A. Louzi. A multilevel stochastic approximation algorithm for unbiased value-at-risk and expected shortfall estimation. Forthcoming in Finance and Stochastics.
- Crépey S., N. Frikha, A. Louzi, and G. Pagès. Asymptotic error analysis of multilevel stochastic approximations for the value-at-risk and expected shortfall. Forthcoming in Electronic Journal of Probability
- De Crescenzo A., Fuhrman M., Kharroubi I., et H. Pham : “Mean field control of non exchan-geable systems “, arXiv : 2407.18635
- Denkert R., H. Pham, et X. Warin : “Control randomisation approach for policy gradient and application to reinforcement learning in optimal switching”, arXiv :2404.17939, en révision à Applied Mathematics and Optimization.
- Frikha N., Germain M., Laurière M., H. Pham et X. Song : Actor-critic learning for mean-field control in continuous time, arXiv :2303.06993
- 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
- Loeper G., O. Mazhar, et H. Pham : “Generative diffusion models : bridging Schrödinger and Bass”, work in progress.
- Mazhar O. et H. Pham : “Non-parametric Estimation of the Drift of a Time Series Schrödinger bridge”, work in progress.
2023
- J. Guyon, J. Lekeufack: Volatility is (mostly) path dependent, Quantitative Finance 23(9):1221–1258, 2023 [SSRN preprint 4174589]
- F. Bourgey, J. Guyon: Fast exact joint S&P 500/VIX smile calibration in discrete and continuous time, to appear in Risk [SSRN preprint 4315084]
- J. Guyon, S. Mustapha: Neural joint S&P 500/VIX smile calibration, to appear in Risk [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]
- H. Pham, X. Warin: Actor critic learning algorithms for mean field control with moment neural networks, [arXiv:2309.04317]
- M. Hamdouche, P. Henry Labordère, H. Pham: Generative modeling for time series via Schrödinger bridge, [arXiv:2304.05093]
- 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], to appear in Applied Mathematical Finance
- N. Frikha, M. Germain, M. Laurière, H. Pham, X. Song: Actor-critic learning for mean-field control in continuous time, [arXiv:2303.06993]
- 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