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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…
Algorithmic market making for options
Bastien Baldacci, Philippe Bergault, Olivier Guéant
In this article, we tackle the problem of a market maker in charge of a book of options on a single liquid underlying asset. By using an approximation of the portfolio in terms of…
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…
Size matters for OTC market makers: general results and dimensionality reduction techniques
Philippe Bergault, Olivier Guéant
In most OTC markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to bu…
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…