Emmanuel Gobet
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View article: Improved Convergence Rate for Reflected BSDEs by Penalization Method
Improved Convergence Rate for Reflected BSDEs by Penalization Method Open
View article: Meta-modelling paths of simple climate models using neural networks and dirichlet polynomials: an application to DICE
Meta-modelling paths of simple climate models using neural networks and dirichlet polynomials: an application to DICE Open
View article: HTGAN: heavy-tail GAN for multivariate dependent extremes via latent-dimensional control
HTGAN: heavy-tail GAN for multivariate dependent extremes via latent-dimensional control Open
Dealing with extreme values is a key challenge in probabilistic modeling, relevant to economics, engineering, and life sciences. Standard GANs, built on light-tailed noise, fail to capture heavy-tail behavior and dependence in extreme regi…
View article: Interpretable seasonal multisite hidden Markov model for stochastic rain generation in France
Interpretable seasonal multisite hidden Markov model for stochastic rain generation in France Open
We present a lightweight stochastic weather generator (SWG) based on a multisite hidden Markov model (HMM) trained on a large area with French weather station data. Our model captures spatiotemporal precipitation patterns with a strong emp…
View article: Optimal exit from Uniswap v3 and best expected return for a liquidity provider
Optimal exit from Uniswap v3 and best expected return for a liquidity provider Open
We analyze the profitability of liquidity providers’ (LPs) positions in Uniswap v3 by aggregating fee income and impermanent loss within an optimal stopping framework. Our first result shows that liquidity burn should be optimized range by…
View article: Statistical Error Bounds for Weighted Mean and Median With Application to Robust Aggregation of Cryptocurrency Data
Statistical Error Bounds for Weighted Mean and Median With Application to Robust Aggregation of Cryptocurrency Data Open
We study price aggregation methodologies applied to crypto‐currency prices with quotations fragmented on different platforms. An intrinsic difficulty is that the price returns and volumes are heavy‐tailed, with many outliers, making averag…
View article: Meta-modelling paths of the DICE climate block using Neural Networks and Dirichlet polynomials
Meta-modelling paths of the DICE climate block using Neural Networks and Dirichlet polynomials Open
Our study focuses on climate models extensively employed in climate science and economicclimate research, which project temperature outcomes from carbon emission trajectories. Addressing the need for rapid evaluation in Integrated Assessme…
View article: Uniswap v3: impermanent loss modeling and swap fees asymptotic analysis
Uniswap v3: impermanent loss modeling and swap fees asymptotic analysis Open
Automated Market Makers have emerged quite recently, and Uniswap is one of the most widely used platforms (it covers 60% of the total value locked on Ethereum blockchain at the time of writing this article). This protocol is challenging fr…
View article: <span>Optimal Exit from Uniswap V3 And Best Expected Return for a Liquidity Provider</span>
<span>Optimal Exit from Uniswap V3 And Best Expected Return for a Liquidity Provider</span> Open
View article: ExcessGAN: simulation above extreme thresholds using Generative Adversarial Networks
ExcessGAN: simulation above extreme thresholds using Generative Adversarial Networks Open
We design a GAN-based generative model for sampling multivariate data exceeding large thresholds, this results in the ExcessGAN algorithm. Our approach is based on approximating marginal log-quantile functions using feedforward neural netw…
View article: ExceedGAN: Simulation above extreme thresholds using Generative Adversarial Networks
ExceedGAN: Simulation above extreme thresholds using Generative Adversarial Networks Open
This paper devises a novel neural-inspired approach for simulating multivariate extremes. Specifically, we propose a GAN-based generative model for sampling multivariate data exceeding large thresholds, giving rise to what we refer to as t…
View article: Corporate probability of default under an energy transition scenario with business model adaptation to the transition
Corporate probability of default under an energy transition scenario with business model adaptation to the transition Open
The energy transition generates for the financial system the so-called 'transition risks', leading to the development of Climate Stress-Tests. We propose a firm-level corporate credit risk model that accounts for business model evolution …
View article: Learning extreme expected shortfall and conditional tail moments with neural networks. Application to cryptocurrency data
Learning extreme expected shortfall and conditional tail moments with neural networks. Application to cryptocurrency data Open
View article: Optimal business model adaptation plan for a company under a transition scenario
Optimal business model adaptation plan for a company under a transition scenario Open
Climate stress-tests aim at projecting the financial impacts of climate change, covering both transition and physical risks under given macro scenarios. However, in practice, transition risk has been the main focus of supervisory and acade…
View article: Numerical approximations of McKean Anticipative Backward Stochastic Differential Equations arising in Initial Margin requirements
Numerical approximations of McKean Anticipative Backward Stochastic Differential Equations arising in Initial Margin requirements Open
We introduce a new class of anticipative backward stochastic differential equations with a dependence of McKean type on the law of the solution, that we name MKABSDE. We provide existence and uniqueness results in a general framework with …
View article: An Efficient SSP-based Methodology for Assessing Climate Risks of a Large Credit Portfolio
An Efficient SSP-based Methodology for Assessing Climate Risks of a Large Credit Portfolio Open
International audience
View article: Quasi-Regression Monte-Carlo scheme for semi-linear PDEs and BSDEs with large scale parallelization on GPUs
Quasi-Regression Monte-Carlo scheme for semi-linear PDEs and BSDEs with large scale parallelization on GPUs Open
In this article we design a novel quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), and we analyze the convergence of the proposed method. The a…
View article: Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs
Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs Open
In this paper, we design a novel algorithm based on Least-Squares Monte Carlo (LSMC) in order to approximate the solution of discrete time Backward Stochastic Differential Equations (BSDEs). Our algorithm allows massive parallelization of …
View article: Numerical approximation of ergodic BSDEs using non linear Feynman-Kac formulas
Numerical approximation of ergodic BSDEs using non linear Feynman-Kac formulas Open
In this work we study the numerical approximation of a class of ergodic Backward Stochastic Differential Equations. These equations are formulated in an infinite horizon framework and provide a probabilistic representation for elliptic Par…
View article: Interpretable Seasonal Hidden Markov Model for spatio-temporal stochastic rain generation in France
Interpretable Seasonal Hidden Markov Model for spatio-temporal stochastic rain generation in France Open
View article: Thorough mathematical modeling and analysis of Uniswap v3
Thorough mathematical modeling and analysis of Uniswap v3 Open
International audience
View article: Simulation of multivariate extreme events with generative models
Simulation of multivariate extreme events with generative models Open
International audience
View article: A Mean Field Game Model for Renewable Investment Under Long-Term Uncertainty and Risk Aversion
A Mean Field Game Model for Renewable Investment Under Long-Term Uncertainty and Risk Aversion Open
View article: Estimation of extreme risk measures with neural networks
Estimation of extreme risk measures with neural networks Open
International audience
View article: Neural networks based learning applied to extreme statistics and sampling rare events
Neural networks based learning applied to extreme statistics and sampling rare events Open
International audience
View article: On the simulation of extreme events with neural networks
On the simulation of extreme events with neural networks Open
National audience
View article: Structured dictionary learning of rating migration matrices for credit risk modeling
Structured dictionary learning of rating migration matrices for credit risk modeling Open
View article: Deep generative modeling of multivariate dependent extremes
Deep generative modeling of multivariate dependent extremes Open
View article: Learning extreme expected shortfall with neural networks
Learning extreme expected shortfall with neural networks Open
International audience
View article: Estimation of extreme expected shortfall with neural networks
Estimation of extreme expected shortfall with neural networks Open
International audience