Patrimony

The Louis Bachelier Group's patrimony has been defined as all the publications produced by academic researchers thanks to Group funding (ILB, FdR, IEF, Labex) or via the use of EquipEx data (BEDOFIH, EUROFIDAI).


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Algorithmic trading in a microstructural limit order book model.

Hawkes Process, High-dimensional stochastic control, High-frequency trading, Limit order book, Local regression, Markov Decision Process, Pure-jump controlled process, Quantization

Algorithmic trading in a microstructural limit order book model.

Hawkes Process, High-dimensional stochastic control, High-frequency trading, Limit order book, Local regression, Markov Decision Process, Pure-jump controlled process, Quantization

Stochastic algorithms for risk management and indexing of media databases.

Apprentissage automatique, Control stochastic, Contrôle stochastique, Exact simulation, Incomplete market, Indexation d'images, Machine learning, Malliavin sensitivity, Marché incomplet, Media indexing, Optimization problem, Problème d'optimisation, Quantification, Quantization, Réduction de variance, Sensibilité par Malliavin, Simulation trajectorielle exacte, Stochastic volatility, Variance reduction, Volatilité stochastique

Numerical methods for piecewise deterministic Markovian processes.

Arrêt optimal, Méthode numérique, Numerical method, Optimal stopping, Piecewise-deterministic Markov process, Processus markovien déterministe par morceaux, Quantification, Quantization

Numerical methods for an optimal multiple stopping problem.

Optimal multiple stopping time problem, Quantization, Swing option

Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications.

Algorithms, Deep learning, Monte- Carlo, Performance iteration, Quantization, Reinforcement learning, Value iterations

A class of finite-dimensional numerically solvable McKean-Vlasov control problems.

Control randomization, Control randomization ˚, McKean-Vlasov control, Polynomial class, Quantization, Regress later, Regress-later

Deep neural networks algorithms for stochastic control problems on finite horizon, part I: convergence analysis.

Deep learning, Dynamic programming, Performance iteration, Quantization

A Class of Finite-Dimensional Numerically Solvable McKean-Vlasov Control Problems.

Control randomization, Control randomization ˚, McKean-Vlasov control, Polynomial class, Quantization, Regress later, Regress-later