One of the key decisions in execution strategies is the choice between a passive (liquidity
providing) or an aggressive (liquidity taking) order to execute a trade in a limit order book …

This paper develops a pairs trading framework based on a mean-reverting jump–diffusion
model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to …

We use a deep neural network to generate controllers for optimal trading on high-frequency
data. For the first time, a neural network learns the map** between the preferences of the …

We characterize the optimal signal-adaptive liquidation strategy for an agent subject to
power-law resilience and zero temporary price impact with a Gaussian signal, which can …

We propose a microstructural modeling framework for studying optimal market-making
policies in a FIFO (first in first out) limit order book (order book). In this context, the limit …

In this work, a generative model based on recurrent neural networks for the complete
dynamics of a limit order book is developed. The model captures the dynamics of the limit …

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 its vega …

The time proximity of high-frequency trades can contain a salient signal. In this paper, we
propose a method to classify every trade, based on its proximity with other trades in the …

Information drives trading and hence affects price dynamics. We study how an informed
trader optimally trades, how multiple traders compete with each other, and how their …

This paper studies optimal market making for large-tick assets in the presence of latency. We
consider a random walk model for the asset price and formulate the market maker's …