Stochastic optimal control and games have a wide range of applications, from finance and
economics to social sciences, robotics, and energy management. Many real-world …

In this bibliometric study, the significant transformations in the financial sector brought about
by automation and technological advancements from 1984 to 2022 are explored. A total of …

The design of trading algorithms requires sophisticated mathematical models backed up by
reliable data. In this textbook, the authors develop models for algorithmic trading in contexts …

In this paper we formulate the now classical problem of optimal liquidation (or optimal
trading) inside a mean field game (MFG). This is a noticeable change since usually …

Constant product markets with concentrated liquidity (CL) are the most popular type of
automated market makers. In this paper, we characterize the continuous-time wealth …

Optimal trade execution is an important problem faced by essentially all traders. Much
research into optimal execution uses stringent model assumptions and applies continuous …

This book exposes and comments on the consequences of Reg NMS and MiFID on market
microstructure. It covers changes in market design, electronic trading, and investor and …

We use high-frequency data from the Nasdaq exchange to build a measure of volume
imbalance in the limit order (LO) book. We show that our measure is a good predictor of the …

In this work we apply the Deep Galerkin Method (DGM) described in Sirignano and
Spiliopoulos (2018) to solve a number of partial differential equations that arise in …

As a fundamental problem in algorithmic trading, order execution aims at fulfilling a specific
trading order, either liquidation or acquirement, for a given instrument. Towards effective …