This information is indicative and can be subject to change. 
Algorithmic trading​
Teacher:  Olivier Guéant 
E-mail: [email protected] 
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.