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
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.
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-requis: Advanced time series, Machine learning, Python 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
