In this review article, we present recent work on the regularity of dynamical market impact
models and their associated optimal order execution strategies. In particular, we address the …

This paper develops a new neural network architecture for modeling spatial distributions (ie
distributions on R d) which is more computationally efficient than a traditional fully …

This review article is intended to collect and summarize many of the results in the field of
optimal execution over the last twenty years. In doing so, we describe the general workings …

We develop a high frequency (HF) trading strategy where the HF trader uses her superior
speed to process information and to post limit sell and buy orders. By introducing a …

Market makers continuously set bid and ask quotes for the stocks they have under
consideration. Hence they face a complex optimization problem in which their return, based …

We propose a framework for studying optimal market-making policies in a limit order book
(LOB). The bid–ask spread of the LOB is modeled by a tick-valued continuous-time Markov …

This paper addresses portfolio liquidation using a new angle. Instead of focusing only on the
scheduling aspect like Almgren and Chriss in [J. Risk, 3 (2000), pp. 5--39], or only on the …

We develop an optimal execution policy for an investor seeking to execute a large order
using limit and market orders. The investor solves the optimal policy considering different …

Market makers provide liquidity to other market participants: they propose prices at which
they stand ready to buy and sell a wide variety of assets. They face a complex optimization …

Algorithmic traders acknowledge that their models are incorrectly specified, thus we allow for
ambiguity in their choices to make their models robust to misspecification in (i) the arrival …