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Liquidity Stress Testing using Optimal Portfolio Liquidation
We find that the optimal terminal time for a linear execution of a small order is proportional to the square root of the ratio between the amount being bought or sold and the average daily volume.
An approximate solution for options market-making in high dimension
Managing a book of options on several underlying involves controlling positions of several thousands of financial assets.
Adaptive trading strategies across liquidity pools
In this article, we provide a flexible framework for optimal trading in an asset listed on different venues.
Market making and incentives design in the presence of a dark pool: a deep reinforcement learning approach
We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange.
Deep reinforcement learning for market making in corporate bonds: beating the curse of dimensionality
These models describe the complex optimization problem faced by market makers: proposing bid and ask prices in an optimal way for making money out of the difference between bid and ask prices while mitigating the market risk associated with holding inventory.
Accelerated Share Repurchase and other buyback programs: what neural networks can bring
When firms want to buy back their own shares, they have a choice between several alternatives.
