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This information is indicative and can be subject to change. 
Algorithmic trading​
Teacher:  Olivier Guéant 
E-mail: olivier.gueant@univ-paris1.fr 
ECTS: 2.5
Evaluation: Comments on an academic paper   
Previsional Place and time:  

Prerequisites:  differential calculus
Aim of the course:
(i) Getting a better knowledge of market microstructure (limit order books, requests for quotes, market fragmentation, etc.)
(ii) Knowing the basic models of optimal execution and market making (Almgren-Chriss and Avellaneda-Stoikov)
 Syllabus: 
Course 1: introduction to financial markets and their microstructure
  • history of markets and models
  • how transactions happen (limit order books, RFQs, RFSs)
  • fragmentation of markets
Course 2: optimal execution in discrete time
  • the Almgren-Chriss model and the sinh formula
Course 3: optimal execution in continuous time
  • Bolza problems, Euler-Lagrange equations and Hamilton-Jacobi PDEs
  • application to the Almgren-Chriss model
Course 4: optimal execution: several extensions 
  • PVol orders, Target close orders
  • models of market impact
Course 5: optimal market making
  • introduction to market making
  • Avellaneda-Stoikov model
Course 6: optimal market making
  • multi-asset extensions
  • applications to FX

References: 
  • Guéant. The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making. 2016.
  • Cartea, Jaimungal, Penalva. Algorithmic and High-Frequency Trading. 2015.



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  • Home
  • Curriculum
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  • About
  • Contact