E. Gobet

发表

Sensitivity Analysis Using It[o-circumflex]--Malliavin Calculus and Martingales, and Application to Stochastic Optimal Control

Rémi Munos, Emmanuel Gobet, R. Munos, 2005, SIAM J. Control. Optim..

Euler schemes and half-space approximation for the simulation of diffusion in a domain

E. Gobet, 2001 .

Local asymptotic mixed normality property for elliptic diffusion: a Malliavin calculus approach

E. Gobet, 2001 .

Weak approximation of killed diffusion using Euler schemes

E. Gobet, 2000 .

LAN property for ergodic diffusions with discrete observations

E. Gobet, 2002 .

Exact approximation rate of killed hypoelliptic diffusions using the discrete Euler scheme

E. Gobet, S. Menozzi, 2004 .

Stopped diffusion processes: Boundary corrections and overshoot

E. Gobet, S. Menozzi, 2007, 0706.4042.

Stochastic Approximation Finite Element Method: Analytical Formulas for Multidimensional Diffusion Process

Emmanuel Gobet, Romain Bompis, E. Gobet, 2014, SIAM J. Numer. Anal..

Asymptotic and Non Asymptotic Approximations for Option Valuation

E. Gobet, R. Bompis, Romain Bompis, 2012 .

Sensitivity analysis using Itô-Malliavin calculus and application to stochastic optimal control

E. Gobet, 2002 .

A CLT for infinitely stratified estimators, with applications to debiased MLMC

P. Glynn, B. Jourdain, B. Bouchard, 2017 .

First time to exit of a continuous Itô process: General moment estimates and L1 -convergence rate for discrete time approximations

B. Bouchard, E. Gobet, S. Geiss, 2013, 1307.4247.

SENSITIVITY ANALYSIS USING ITÔ – MALLIAVIN CALCULUS AND

E. Gobet, 2002 .

Numerical approximations of McKean anticipative backward stochastic differential equations arising in initial margin requirements

E. Gobet, A. Agarwal, S. De Marco, 2019, ESAIM: Proceedings and Surveys.

1 Fractional smoothness and applications in Finance

E. Gobet, S. Geiss, 2010 .

L2-time regularity of BSDEs with irregular terminal functions

Emmanuel Gobet, Azmi Makhlouf, E. Gobet, 2010 .

Rare event simulation related to financial risks: efficient estimation and sensitivity analysis

Ankush Agarwal, Emmanuel Gobet, Stefano De Marco, 2017 .

Nonparametric estimation of scalar diffusions based on low frequency data

M. Hoffmann, E. Gobet, M. Reiß, 2002, math/0503680.

A regression-based Monte Carlo method to solve backward stochastic differential equations

E. Gobet, X. Warin, Jean-Philippe Lemor, 2005, math/0508491.

Optimal discretization of stochastic integrals driven by general Brownian semimartingale

E. Gobet, Uladzislau Stazhynski, 2018, Annales de l'Institut Henri Poincaré, Probabilités et Statistiques.

Revisiting the Greeks for European and American Options

E. Gobet, 2004 .

Monte Carlo Evaluation of Greeks for Multidimensional Barrier and Lookback Options

E. Gobet, A. Kohatsu-Higa, G. Bernis, 2003 .

Rate of convergence of an empirical regression method for solving generalized backward stochastic differential equations

E. Gobet, X. Warin, Jean-Philippe Lemor, 2006 .

Numerical Methods for the Pricing of Swing Options: A Stochastic Control Approach

Rémi Munos, Emmanuel Gobet, Charles Dossal, 2006 .

A generative model for fBm with deep ReLU neural networks

S. Girard, E. Gobet, Michaël Allouche, 2022, J. Complex..

Approximation of backward stochastic differential equations using Malliavin weights and least-squares regression

Emmanuel Gobet, Plamen Turkedjiev, E. Gobet, 2016, 1601.01186.

Sharp estimates for the convergence of the density of the Euler scheme in small time

Céline Labart, Emmanuel Gobet, E. Gobet, 2008 .

Adaptive importance sampling in least-squares Monte Carlo algorithms for backward stochastic differential equations

Emmanuel Gobet, E. Gobet, P. Turkedjiev, 2017 .

Analytical approximations of local‐Heston volatility model and error analysis

E. Gobet, R. Bompis, Romain Bompis, 2018 .

Expansion formulas for European options in a local volatility model

Eric Benhamou, Emmanuel Gobet, Mohammed Miri, 2010 .

EXPANSION FORMULAS FOR BIVARIATE PAYOFFS WITH APPLICATION TO BEST-OF OPTIONS ON EQUITY AND INFLATION

E. Gobet, Julien Hok, 2014 .

2 2 Fe b 20 06 Error expansion for the discretization of Backward Stochastic Differential Equations

E. Gobet, C. Labart, 2006 .

Discrete Sampling of Functionals of Ito Processes

Emmanuel Gobet, Stéphane Menozzi, E. Gobet, 2007 .

Analytical Approximations of BSDEs with Non-Smooth Driver

E. Gobet, S. Pagliarani, 2014 .

Advanced Monte Carlo Methods for Barrier and Related Exotic Options

Emmanuel Gobet, E. Gobet, 2008 .

Generalized fractional smoothness and Lp-variation of BSDEs with non-Lipschitz terminal condition

Emmanuel Gobet, Stefan Geiss, Christel Geiss, 2011, 1103.0371.

Fractional smoothness of functionals of diffusion processes under a change of measure

E. Gobet, S. Geiss, 2012, 1210.4572.

Discrete time hedging errors for options with irregular payoffs

Emmanuel Gobet, Emmanuel Temam, E. Gobet, 2001, Finance Stochastics.

Option valuation and hedging using an asymmetric risk function: asymptotic optimality through fully nonlinear partial differential equations

E. Gobet, X. Warin, Isaque Pimentel, 2020, Finance and Stochastics.

Fractional Smoothness and Applications in Finance

Emmanuel Gobet, Stefan Geiss, E. Gobet, 2010, 1004.3577.

Analytical Approximations of BSDEs with Non-Smooth Driver

Stefano Pagliarani, Emmanuel Gobet, E. Gobet, 2014, SIAM J. Financial Math..

Introduction: Brief Overview of Monte-Carlo Methods

Emmanuel Gobet, E. Gobet, 2016 .

Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear

Emmanuel Gobet, E. Gobet, 2016 .

Introduction to stochastic calculus and to the resolution of PDEs using Monte Carlo simulations - Lectures notes of XV Spanish-French School on Numerical Simulation in Physics and Engineering

Emmanuel Gobet, E. Gobet, 2012 .

Linear regression MDP scheme for discrete backward stochastic differential equations under general conditions

Emmanuel Gobet, Plamen Turkedjiev, E. Gobet, 2015, Math. Comput..

A new sequential algorithm for L2-approximation and application to Monte-Carlo integration

E. Gobet, K. Surana, 2014 .

Weak approximation of averaged diffusion processes

Emmanuel Gobet, Mohammed Miri, E. Gobet, 2014 .

Weak approximations and VIX option price expansions in forward variance curve models

E. Gobet, S. Marco, Florian Bourgey, 2022, Quantitative Finance.

Quasi-Regression Monte-Carlo Scheme for Semi-Linear PDEs and BSDEs with Large Scale Parallelization on GPUs

Emmanuel Gobet, Carlos Vázquez, José Germán López-Salas, 2019, Archives of Computational Methods in Engineering.

Strong approximation of stochastic processes at random times and application to their exact simulation

E. Gobet, M. Mrad, 2017 .

Quantification d'incertitude pour l'Approximation Stochastique

E. Gobet, G. Fort, S. Crépey, 2019 .

Day-ahead probabilistic forecast of solar irradiance: a Stochastic Differential Equation approach

E. Gobet, J. Badosa, Maxime Grangereau, 2017 .

Parametric inference for diffusions observed at stopping times

E. Gobet, Uladzislau Stazhynski, 2020, Electronic Journal of Statistics.

Nonparametric estimation of scalar diffusions based on low frequency data

M. Hoffmann, E. Gobet, M. Reiß, 2002, math/0503680.

A regression-based Monte Carlo method to solve backward stochastic differential equations

E. Gobet, X. Warin, Jean-Philippe Lemor, 2005, math/0508491.

Unbiasing and robustifying implied volatility calibration in a cryptocurrency market with large bid-ask spreads and missing quotes

E. Gobet, M. Echenim, Anne-Claire Maurice, 2022, 2207.02989.

Optimal ecological transition path of a credit portfolio distribution, based on multidate Monge–Kantorovich formulation

E. Gobet, Fanny Cartellier, C. Lage, 2023, Annals of Operations Research.

A sequential Monte Carlo algorithm for solving BSDEs

E. Gobet, C. Labart, 2007 .

Volatility Uncertainty Quantification in a Stochastic Control Problem Applied to Energy

E. Gobet, J. Printems, Francisco Bernal, 2019, Methodology and Computing in Applied Probability.

ALMOST SURE OPTIMAL HEDGING STRATEGY 1

E. Gobet, Nicolas Landon, 2014 .

Nonparametric estimation of scalar diffusions based on low frequency data

M. Hoffmann, E. Gobet, M. Reiß, 2002, math/0503680.

Model-adaptive optimal discretization of stochastic integrals*

E. Gobet, Uladzislau Stazhynski, 2018, Stochastics.

Learning Value-at-Risk and Expected Shortfall

E. Gobet, S. Crépey, Hoang Nguyen, 2022, 2209.06476.

Smart expansion and fast calibration for jump diffusions

E. Gobet, E. Benhamou, M. Miri, 2007, Finance Stochastics.

Estimation of extreme quantiles from heavy-tailed distributions with neural networks

S. Girard, E. Gobet, Michael Allouche, 2023, Statistics and Computing.

Newton Method for Stochastic Control Problems

E. Gobet, M. Grangereau, 2022, SIAM Journal on Control and Optimization.

A Comparative Study of Polynomial-Type Chaos Expansions for Indicator Functions

E. Gobet, C. Rey, Florian Bourgey, 2022, SIAM/ASA J. Uncertain. Quantification.

MONTE CARLO EVALUATION OF GREEKS FOR MULTIDIMENSIONAL BARRIER AND LOOKBACK OPTIONS GUILLAUME BERNIS CAI-Fixed Income, Banque CPR, Paris

E. Gobet, 2002 .

Analytical Approximation of Variable Annuities for Small Volatility and Small Withdrawal

E. Gobet, T. B. Zineb, 2017 .

Quasi-Regression Monte-Carlo Scheme for Semi-Linear PDEs and BSDEs with Large Scale Parallelization on GPUs

E. Gobet, C. Vázquez, J. López-Salas, 2019, Archives of Computational Methods in Engineering.

Parameter estimation of Ornstein–Uhlenbeck process generating a stochastic graph

E. Gobet, Gustaw Matulewicz, 2016, Statistical Inference for Stochastic Processes.

Price expansion formulas for model combining local and stochastic volatility

E. Gobet, R. Bompis, 2013 .

Boundary Sensitivities for Diffusion Processes in Time Dependent Domains

E. Gobet, N. Karoui, C. Costantini, 2006 .

A symmetrized Euler scheme for an efficient approximation of reflected diffusions

Mireille Bossy, Denis Talay, Emmanuel Gobet, 2004, Journal of Applied Probability.

Transform MCMC Schemes for Sampling Intractable Factor Copula Models

Rodrigo S. Targino, E. Gobet, Cyril Bénézet, 2023, Methodology and Computing in Applied Probability.

Study of new rare event simulation schemes and their application to extreme scenario generation

Gang Liu, Ankush Agarwal, Emmanuel Gobet, 2018, Math. Comput. Simul..

Generalization bounds for nonparametric regression with $\beta-$mixing samples

Emmanuel Gobet, David Barrera, E. Gobet, 2021, 2108.00997.

Quantitative bounds for concentration-of-measure inequalities and empirical regression: The independent case

David Barrera, Emmanuel Gobet, E. Gobet, 2019, J. Complex..

A NON-INTRUSIVE STRATIFIED RESAMPLER FOR REGRESSION MONTE CARLO: APPLICATION TO SOLVING NON-LINEAR EQUATIONS

Emmanuel Gobet, Jorge Zubelli, E. Gobet, 2018 .

Bridging socioeconomic pathways of $$\textrm{CO}_2$$ emission and credit risk

E. Gobet, Y. Jiao, Florian Bourgey, 2022, Annals of Operations Research.

Metamodel of a Large Credit Risk Portfolio in the Gaussian Copula Model

Emmanuel Gobet, Florian Bourgey, Clément Rey, 2020, SIAM J. Financial Math..

Approximation of discrete BSDE using least-squares regression

Emmanuel Gobet, Plamen Turkedjiev, E. Gobet, 2011 .

Mathematics and Finance

M. Yor, G. Pagès, E. Gobet, 2008 .

Discretization and simulation for a class of SPDEs with applications to Zakai and McKean-Vlasov equations

G. Pagès, H. Pham, E. Gobet, 2004 .

Efficient schemes for the weak approximation of reflected diffusions

Emmanuel Gobet, E. Gobet, 2001, Monte Carlo Methods Appl..

A Nonintrusive Stratified Resampler for Regression Monte Carlo: Application to Solving Nonlinear Equations

Gang Liu, Jorge P. Zubelli, Emmanuel Gobet, 2018, SIAM J. Numer. Anal..

Uncertainty Quantification for Stochastic Approximation Limits Using Chaos Expansion

Gersende Fort, Emmanuel Gobet, Stéphane Crépey, 2020, SIAM/ASA J. Uncertain. Quantification.

Analytical approximations of non-linear SDEs of McKean–Vlasov type

E. Gobet, S. Pagliarani, 2018, Journal of Mathematical Analysis and Applications.

Analytical Approximations of Non-Linear SDEs of McKean-Vlasov Type

E. Gobet, S. Pagliarani, Stefano Pagliarani, 2017, Journal of Mathematical Analysis and Applications.

Almost sure optimal hedging strategy

E. Gobet, Nicolas Landon, 2014, 1405.4170.

EV-GAN: Simulation of extreme events with ReLU neural networks

S. Girard, E. Gobet, Michael Allouche, 2022, J. Mach. Learn. Res..

MCMC design-based non-parametric regression for rare event. Application to nested risk computations

Gersende Fort, Eric Moulines, Emmanuel Gobet, 2017, Monte Carlo Methods Appl..

Discretization and Simulation of the Zakai Equation

Huyên Pham, Gilles Pagès, Jacques Printems, 2006, SIAM J. Numer. Anal..

A power plant valuation under an asymmetric risk criterion taking into account maintenance costs

E. Gobet, C. Alasseur, X. Warin, 2019 .

Parameter estimation of Ornstein–Uhlenbeck process generating a stochastic graph

E. Gobet, Gustaw Matulewicz, 2017 .

Stochastic Linear Programming

E. Gobet, Mrs. J. Evangeline Cicelia, Dr. K. Ramanathan, 2022 .

Rare Event Simulation Using Reversible Shaking Transformations

Gang Liu, Emmanuel Gobet, E. Gobet, 2015, SIAM J. Sci. Comput..

Asymptotic Equivalence Between Boundary Perturbations and Discrete Exit Times: Application to Simulation Schemes

E. Gobet, 2012 .

Stopped diffusion processes: Overshoots and Boundary correction

Emmanuel Gobet, Stéphane Menozzi, E. Gobet, 2007 .

Perturbation of Ornstein-Uhlenbeck stationary distributions: expansion and simulation

E. Gobet, Qihao She, 2016 .

Asymptotic analysis of different covariance matrices estimation for minimum variance portfolio

E. Gobet, Jean-Philippe Lemor, Linda Chamakh, 2023 .

Orlicz Random Fourier Features

Zoltán Szabó, Emmanuel Gobet, Linda Chamakh, 2020, J. Mach. Learn. Res..

Convergence rate of strong approximations of compound random maps

E. Gobet, M. Mrad, 2016 .

Error expansion for the discretization of backward stochastic differential equations

Emmanuel Gobet, E. Gobet, C. Labart, 2006, math/0602503.

Sequential Control Variates for Functionals of Markov Processes

Sylvain Maire, Emmanuel Gobet, E. Gobet, 2005, SIAM J. Numer. Anal..

Smart expansion and fast calibration for jump diffusions

E. Gobet, E. Benhamou, M. Miri, 2007, Finance Stochastics.

LAMN property for hidden processes: The case of integrated diffusions

E. Gobet, A. Gloter, 2007, 0707.0257.

Preliminary control variates to improve empirical regression methods

Emmanuel Gobet, Tarik Ben Zineb, E. Gobet, 2013, Monte Carlo Methods Appl..

Arbitrage free cointegrated models in gas and oil future markets

E. Gobet, Gr'egory Benmenzer, Céline Jérusalem, 2007, 0712.3537.

Extended McKean-Vlasov optimal stochastic control applied to smart grid management

Emmanuel Gobet, Maxime Grangereau, E. Gobet, 2019, ESAIM: Control, Optimisation and Calculus of Variations.

A spectral Monte Carlo method for the Poisson equation

Sylvain Maire, Emmanuel Gobet, E. Gobet, 2004, Monte Carlo Methods Appl..

Price expansion formulas for model combining local and stochastic volatility

E. Gobet, Romain Bompis, 2013 .

Time Dependent Heston Model

Eric Benhamou, Emmanuel Gobet, Mohammed Miri, 2009, SIAM J. Financial Math..

BSDEs and fractional smoothness

E. Gobet, C. Geiss, S. Geiss, 2011 .