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ARTHUR BAGOURD - FX Algo Trading Quant, Barclays London

GAELLE LE FOL - Professor in Finance, Head of the Master 203, Université Paris - Dauphine

JIANG PU - Enseignant-Chercheur, Ecole Supérieure d'Ingénieurs Léonard de Vinci

Les objectifs du cours

This course is a presentation of financial markets, trading mechanisms and their evolution dedicated to advancing the understanding and practice of electronic markets. A particular attention will be dedicated to optimal trading and execution technics but also on the use of algo trading startegies by market participants (who do what).

There also will be 2 invited sessions where some professionnals will come to explain their use of Algos and electronic markets in their day-to-day work: Samy-Adrien Akoun, systematic/quant trader at Citadel Securities and  Julia Berthou, Investable Index Solution at JP Morgan.


Les étudiants doivent être inscrits aux cours d'Evaluation de dérivés et calcul stochastique 2 et de Finance numérique et avoir validé Evaluation de dérivés et Calcul stochastique 1 et Investissements et marchés financiers.

Plan du course

Session 1 (1h30): Definitions, Evolution of financial markets & regulation, Traders/investors and algo trading businesses (Execution, Market Making, Investing)

Session 2 (1h30): Algorithms type, objectives, uses and users.

Session 3 (1h30): Orders, strategies, trading platforms and smart orders rooters.

Session 4 (1h30): Tradinc Cost (TCA) and Performance Analyses

Session 5 (3h) : Using algos for Investing and Market making

Session 6 (3h): Execution algo introduction + Around the Almgren-Chriss model

Session 7 (3h): Execution algo - Dynamic programming and trading strategies

Session 8 (3h): Execution algo - Limit order book and market making

Session 9 (3h): Execution algo - Reinforcement learning and beyond

Pré-requisAdvanced time seriesMachine learningPython or C++ programming


Bacidore, J. R., 2020, Algorithmic Trading Method: A practitioner's guide, TBG Press New York, 229 pages.

Chan E., Algorithmic Trading- Winning Strategies and Their Rationale, Wiley, 2013, 207 pages.

Guéant O., 2016, The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making, Chapman and Hall, 302 pages.

Kissell, R., 2020 Algorithmic Trading Method: Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques, Academic Press Inc, 2nd Edition, 612 pages.

Lehalle C. A. and S. Laruelle, 2018, Market Microstructure in Pratice, World Scientific, 2nd Edition, 339 pages.

Johnson B, 2010, Algorithmic Trading & DMA, Myeloma Press, 574 pages.


Group project (Teams of 2 students). 2 projects will be proposed.

Evaluation: Report + presentation