An overall view of key problems in algorithmic trading and recent progress

Abstract

We summarize the fundamental issues at stake in algorithmic trading, and the progress made in this field over the last twenty years. We first present the key problems of algorithmic trading, describing the concepts of optimal execution, optimal placement, and price impact. We then discuss the most recent advances in algorithmic trading through the use of Machine Learning, discussing the use of Deep Learning, Reinforcement Learning, and Generative Adversarial Networks.

Michaël Karpe
Michaël Karpe
Machine Learning Scientist

Machine Learning Scientist at Next Gate Tech. MEng in Industrial Engineering & Operations Research, FinTech Concentration at University of California, Berkeley. Diplôme d’Ingénieur (MSc) in Applied Mathematics & Computer Science, Machine Learning & Computer Vision Concentration at Ecole des Ponts ParisTech, France.