Electronic Markets

Ects : 3

Enseignant responsable :

Volume horaire : 21

Description du contenu de l'enseignement :

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 strategies by market participants (who do what).

 

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

 

Session 2: Algorithms type, objectives, uses and users

 

Session 3: Orders, strategies, trading platforms and smart orders rooters

 

Session 4: Tradinc Cost (TCA) and Performance Analyses

 

Session 5: Using algos for investing and market making

 

Session 6: Introduction to execution Algo + Around the Almgren-Chriss model

 

Session 7: Dynamic programming and trading strategies

 

Session 8: Limit order book and market making

 

Session 9: Reinforcement learning and beyond

Pré-requis recommandés :

Derivative Pricing and Stochastic Calculus 2, Computational Finance, Advanced time series, Machine learning,

Coefficient : 1.5

Compétence à acquérir :

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).

Mode de contrôle des connaissances :

Group project: report + defense (individual evaluation)

Bibliographie, lectures recommandées

  • Almgren R. and N. Chriss. Optimal execution of portfolio transactions. Journal of Risk, 3(2):5–39, 2000.
  • 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.
  • Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. Adaptive computation and machine learning, MIT Press, Second edn. (2018).