DENIS Laurent

Laurent DENIS

Professeur des universités
tél: (33) 2 43 83 32 17
email (ldenis @ univ-lemans.fr)

Laboratoire Manceau de Mathématiques                                                         
Le Mans Université
Bâtiment IRA
Avenue Olivier Messiaen
72085 LE MANS Cédex
FRANCE

Directeur du LMM (Laboratoire Manceau de Mathématiques)
Responsable de la double licence en mathématiques et économie
Professeur Chargé de Cours à l'Ecole Polytechnique

Domains of interest

• Uncertain models in finance
• Non-linear expectation
• Stochastic Partial Differential Equations
• Malliavin calculus for jump processes
• Dirichlet forms

Publications

© 2015

Dirichlet Forms Methods for Poisson Point Measures and Lévy Processes

With Emphasis on the Creation-Annihilation Techniques

Presents a new approach to absolute continuity and regularity of laws of Poisson functionals 

Selected papers on SPDEs

• Denis L., Matoussi A., Zhang J. The existence and uniqueness result for Quasilinear Stochastic PDEs with Obstacle under weaker integrability conditions, preprint (available on arXiv).
• Denis L., Matoussi A., Zhang J. Maximum Principle for Quasilinear Stochastic PDEs with Obstacle, to appear in Electronic Journal of Probability (available on arXiv).
• Denis L., Matoussi A., Zhang J. The obstacle Problem for Quasilinear Stochastic PDEs:analytical approach, Annals of Probability , Vol. 42, No. 3, 865-905 (2014)  (arXiv version).
• Denis L., Matoussi A. Maximum principle for  quasilinear SPDE's on a bounded  domain without regularity assumptions, Stochastic Processes and their Applications, Vol. 123  (3), pp 1104-1137 (2013).
• Denis L., Matoussi A. et  Stoica, I. L., Maximum principle and comparison theorem for quasilinear Stochastic PDE's, , Electronic Journal of Probability Vol. 14 (2009).
• Denis L., Matoussi A. et  Stoica, I. L., Maximum principle for parabolic SPDE's: first approach, Proceeding "Stochastic Partial Differential Equations and Applications – VIII: Levico, Jan. 6-12, 2008”, edited by Dipartimento di Matematica Seconda Università di Napoli (2009) (pdf version) .
• Denis L., Matoussi A. et  Stoica, I. L.  L^p estimates for the uniform norm of solutions of quasilinear SPDE’s, Probability Theory and Related Fields 113, pp. 437-463 (2005).
• Denis L., Stoica, I. L., A general analytical result for non-linear s.p.d.e.'s and applications, Electronic Journal of Probability, Vol. 9, p. 674-709 (2004).

Selected papers on mathematical finance

• Denis L. et Nguyen T.M., Malliavin calculus for Markov chains using perturbations of time, (preprint).
• Denis L. et Kervarec M., Utility functions and optimal investment in non-dominated models, SIAM Journal on control and optimization, Vol. 51 n°3, pp 1803-1822 (2013).
• Denis L., Hu Y et Peng S. , Function spaces and capacity related to a Sublinear Expectation: application to G-Brownian Motion Paths,  Potential Analysis, Vol. 34 n°2 (2011) 139-161.
• Denis L., Fernandez B., Meda A., Estimation of value at risk and ruin probability for diffusion processes with jumps, Mathematical Finance Vol. 19 N°2, pp281-302 (2009).
• Denis L. et Martini C.,  A theoretical framework for the pricing of contingent claims in the presence of model uncertainty ,  Annals of Applied Probability, Vol. 16 N° 2, pp 827-852 (2006).
• Denis L.,  Grorud A. et  Pontier M.,  Formes de Dirichlet sur un espace de Wiener-Poisson. Application au grossissement de filtration. Séminaire de Probabilités 34, (1999).

Selected papers on Malliavin calculus for jump processes and the "lent particle method"

• Bouleau N. et Denis L. Chaotic extensions and the lent particle method for Brownian motion, Electronic Journal of Probability Vol.18 n°56 (2013).
• Bouleau N., Denis L. Iteration of the lent particle method to existence of smooth densities of Poisson functionals, Potential Analysis 38, pp 169-205 (2013).
• Bouleau N., Denis L., Application of the lent particle method to Poisson driven SDE's, Probability Theory Relat. Fields 151(3–4), 403–433 (2011) .
• Bouleau N., Denis L., Energy image density property and the lent particle method for Poisson  measures,  Jour. of Functional Analysis 257 (2009) 1144-1174.
• Denis L.  A criterion of density for solutions of Poisson-driven SDE's, Probab. Theory and Relat. Fields 118, 406-426 (2000).