8 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
Market making and incentives design in the presence of a dark pool: a deep reinforcement learning approach
Bastien Baldacci, Iuliia Manziuk, Thibaut Mastrolia +1
We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make-take fees policy to attra…
Deep reinforcement learning for market making in corporate bonds: beating the curse of dimensionality
Olivier Guéant, Iuliia Manziuk
In corporate bond markets, which are mainly OTC markets, market makers play a central role by providing bid and ask prices for a large number of bonds to asset managers from all ar…
Accelerated Share Repurchase and other buyback programs: what neural networks can bring
Olivier Guéant, Iuliia Manziuk, Jiang Pu
When firms want to buy back their own shares, they have a choice between several alternatives. If they often carry out open market repurchase, they also increasingly rely on banks…
Optimal control on graphs: existence, uniqueness, and long-term behavior
Olivier Guéant, Iuliia Manziuk
The literature on continuous-time stochastic optimal control seldom deals with the case of discrete state spaces. In this paper, we provide a general framework for the optimal cont…