Search Results for author: Ludovic Tangpi

Found 8 papers, 1 papers with code

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

no code implementations12 Feb 2024 Mathieu Laurière, Ludovic Tangpi, Xuchen Zhou

By passing to the limit, a game with a continuum of players is obtained, in which the interactions are through a graphon.

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

no code implementations21 Jul 2023 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.

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

1 code implementation8 Sep 2022 Ludovic Tangpi, Shichun Wang

In particular, we consider two types of crashes: an endogenous burst which results from excessive selling, and an exogenous burst which cannot be anticipated and is independent from the actions of the traders.

Optimal Investment in a Large Population of Competitive and Heterogeneous Agents

no code implementations23 Feb 2022 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 through a graphon (see definition below).

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

no code implementations24 Nov 2021 Jiarui Chu, Ludovic Tangpi

In this paper we will study the approximation of arbitrary law invariant risk measures.

Maximum principle for stochastic control of SDEs with measurable drifts

no code implementations15 Jan 2021 Olivier Menoukeu-Pamen, Ludovic Tangpi

To achieve this, we first derive an explicit representation of the first variation process (in Sobolev sense ) of the controlled diffusion.

Optimization and Control

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

no code implementations23 Mar 2020 Daniel Bartl, Ludovic Tangpi

Let $\rho$ be a general law--invariant convex risk measure, for instance the average value at risk, and let $X$ be a financial loss, that is, a real random variable.

Duality for pathwise superhedging in continuous time

no code implementations8 May 2017 Daniel Bartl, Michael Kupper, David J. Prömel, Ludovic Tangpi

If the sample space is stable under stopping, the probabilistic problem reduces to finding the supremum over all martingale measures with compact support.

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