activity
20132026
most citedDuality for increasing convex functionals with countably many marginal constraints

18 citations · 63 across the 38 of their papers we have counts for

collaborators

47 papers

math.OC2026

Optimal transportation under McKean-Vlasov dynamics

Camilo Hernández, Ludovic Tangpi

We study a broad class of stochastic transport problems under controlled McKean-Vlasov dynamics, allowing control of both drift and volatility, with weak terminal constraints. In c…

math.PR2025

Marginal flows of non-entropic weak Schrödinger bridges

Camilo Hernández, Ludovic Tangpi

This paper introduces a dynamic formulation of divergence-regularized optimal transport with weak targets on the path space. In our formulation, the classical relative entropy pena…

math.PR2025

Conditional McKean-Vlasov control

René Carmona, Ludovic Tangpi, Kaiwen Zhang

Conditional McKean-Vlasov control problems involve controlling McKean-Vlasov diffusions where the interaction occurs through the law of the state process conditionally on it stayin…

math.PR2025

Particle system approximation of Nash equilibria in large games

Ludovic Tangpi, Nizar Touzi

We develop a probabilistic framework to approximate Nash equilibria in symmetric -player games in the large population regime, via the analysis of associated mean field games (M…

math.OC2024

Pasting of Equilibria and Donsker-type Results for Mean Field Games

Jodi Dianetti, Max Nendel, Ludovic Tangpi +1

This paper studies the relation between equilibria in single-period, discrete-time and continuous-time mean field game models. First, for single-period mean field games, we establi…

math.PR2024

Interacting particle systems on sparse -random graphs

Carla Crucianelli, Ludovic Tangpi

We consider a general interacting particle system with interactions on a random graph, and study the large population limit of this system. When the sequence of underlying graphs c…

math.OC2024

A policy iteration algorithm for non-Markovian control problems

Dylan Possamaï, Ludovic Tangpi

In this paper, we propose a new policy iteration algorithm to compute the value function and the optimal controls of continuous time stochastic control problems. The algorithm reli…

math.OC2024

A Probabilistic Approach to Discounted Infinite Horizon and Invariant Mean Field Games

René Carmona, Ludovic Tangpi, Kaiwen Zhang

This paper considers discounted infinite horizon mean field games by extending the probabilistic weak formulation of the game as introduced by Carmona and Lacker (2015). Under simi…

math.PR2024

Mean field games with common noise via Malliavin calculus

Ludovic Tangpi, Shichun Wang

We present a simpler proof of the existence of equilibria for a class of mean field games with common noise, where players interact through the conditional law given the current va…

math.OC2024

A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents

Mathieu Laurière, Ludovic Tangpi, Xuchen Zhou

Graphon games have been introduced to study games with many players who interact through a weighted graph of interaction. By passing to the limit, a game with a continuum of player…

math.PR2023

On the population size in stochastic differential games

Dylan Possamaï, Ludovic Tangpi

Commuters looking for the shortest path to their destinations, the security of networked computers, hedge funds trading on the same stocks, governments and populations acting to mi…

q-fin.MF2023★ 2 cited

Optimal Bubble Riding with Price-dependent Entry: a Mean Field Game of Controls with Common Noise

Ludovic Tangpi, Shichun Wang

In this paper we further extend the optimal bubble riding model proposed by Tangpi and Wang by allowing for price-dependent entry times. Agents are characterized by their individua…

math.PR2023

Propagation of chaos for mean field Schrödinger problems

Camilo Hernández, Ludovic Tangpi

In this work, we study the mean field Schrödinger problem from a purely probabilistic point of view by exploiting its connection to stochastic control theory for McKean-Vlasov diff…

math.PR2023

Quantitative convergence for displacement monotone mean field games with controlled volatility

Joe Jackson, Ludovic Tangpi

We study the convergence problem for mean field games with common noise and controlled volatility. We adopt the strategy recently put forth by Laurière and the second author, using…

q-fin.MF2022★ 1 cited

Optimal Bubble Riding: A Mean Field Game with Varying Entry Times

Ludovic Tangpi, Shichun Wang

Recent financial bubbles such as the emergence of cryptocurrencies and "meme stocks" have gained increasing attention from both retail and institutional investors. In this paper, w…

math.PR2022

A probabilistic approach to vanishing viscosity for PDEs on the Wasserstein space

Ludovic Tangpi

In this work we prove an analogue, for partial differential equations on the space of probability measures, of the classical vanishing viscosity result known for equations on the E…

q-fin.MF2022

Optimal Investment in a Large Population of Competitive and Heterogeneous Agents

Ludovic Tangpi, Xuchen Zhou

This paper studies a stochastic utility maximization game under relative performance concerns in finite agent and infinite agent settings, where a continuum of agents interact thro…

q-fin.RM2021

Non-asymptotic estimation of risk measures using stochastic gradient Langevin dynamics

Jiarui Chu, Ludovic Tangpi

In this paper we will study the approximation of arbitrary law invariant risk measures. As a starting point, we approximate the average value at risk using stochastic gradient Lang…

math.PR2021★ 2 cited

Non-asymptotic convergence rates for mean-field games: weak formulation and McKean-Vlasov BSDEs

Dylan Possamaï, Ludovic Tangpi

This work is mainly concerned with the so-called limit theory for mean-field games. Adopting the weak formulation paradigm put forward by Carmona and Lacker, we consider a fully no…

math.PR2021

Laplace principle for large population games with control interaction

Peng Luo, Ludovic Tangpi

This work investigates continuous time stochastic differential games with a large number of players, whose costs and dynamics interact through the empirical distribution of both th…

math.OC2021

Maximum principle for stochastic control of SDEs with measurable drifts

Olivier Menoukeu-Pamen, Ludovic Tangpi

In this paper, we consider stochastic optimal control of systems driven by stochastic differential equations with irregular drift coefficient. We establish a necessary and sufficie…

math.PR2020★ 7 cited

Convergence of large population games to mean field games with interaction through the controls

Mathieu Laurière, Ludovic Tangpi

This work considers stochastic differential games with a large number of players, whose costs and dynamics interact through the empirical distribution of both their states and thei…

math.PR2020

Quadratic transportation inequalities for SDEs with measurable drift

Khaled Bahlali, Soufiane Mouchtabih, Ludovic Tangpi

Let X be the solution of the multidimensional stochastic differential equationdX(t) = b(t, X(t)) dt + sigma(t, X(t)) dW(t)\, with X(0)=x where W is a standard Brownian motion. We s…

q-fin.RM2020

Non-asymptotic convergence rates for the plug-in estimation of risk measures

Daniel Bartl, Ludovic Tangpi

Let be a general law--invariant convex risk measure, for instance the average value at risk, and let be a financial loss, that is, a real random variable. In practice, eith…