8 citations · 9 across the 3 of their papers we have counts for
7 papers
Liquidity Stress Testing using Optimal Portfolio Liquidation
Mike Weber, Iuliia Manziuk, Bastien Baldacci
We build an optimal portfolio liquidation model for OTC markets, aiming at minimizing the trading costs via the choice of the liquidation time. We work in the Locally Linear Order…
An approximate solution for options market-making in high dimension
Bastien Baldacci, Joffrey Derchu, Iuliia Manziuk
Managing a book of options on several underlying involves controlling positions of several thousands of financial assets. It is one of the most challenging financial problems invol…
Adaptive trading strategies across liquidity pools
Bastien Baldacci, Iuliia Manziuk
In this article, we provide a flexible framework for optimal trading in an asset listed on different venues. We take into account the dependencies between the imbalance and spread…
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…