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 …

Using a large-scale Deep Learning approach applied to a high-frequency database
containing billions of market quotes and transactions for US equities, we uncover …

Limit order books (LOBs) match buyers and sellers in more than half of the world's financial
markets. This survey highlights the insights that have emerged from the wealth of empirical …

We propose a dynamical theory of market liquidity that predicts that the average
supply/demand profile is V shaped and vanishes around the current price. This result is …

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 …

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 …

Through the analysis of a dataset of ultra high frequency order book updates, we introduce a
model which accommodates the empirical properties of the full order book together with the …

This study provides explicit formulas for the moments and the autocorrelation function of the
number of jumps over a given interval for a self‐excited Hawkes process. These …

We present a bibliometric literature review of the research conducted in the field of Market
Microstructure over the past two decades. Covering 981 articles from the Web of Science …

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 …