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This information is indicative and can be subject to change. 
Stochastic algorithm and approximation for finance 
Teacher:  Noufel Frikha 

E-mail:  [email protected]
ECTS: 2.5
Evaluation: written exam and/or project  
Previsional Place and time:  

Prerequisites: 
  • Probability Theory
  • Stochastic calculus
  • Financial mathematics 
Aim of the course: This course focuses on the important theoretical and practical problem of model calibration in quantitative finance. We will introduce different financial models that are commonly used, present their theoretical properties as well as several numerical methods to compute their parameters. 
 Syllabus: 
  • The Black-Scholes model and the implied volatility
  • Local volatility models and Dupire’s implicit diffusion
  • Stochastic volatility models and the implied volatility
  • Some computational methods in derivatives pricing and model calibration

 
References: 
  • J. Gatheral: The volatility surface, a practitioner’s guide,  Wiley Finance, 2006.
  • B. Dupire, Pricing with a smile, RISK, 7 (1994), pp. 18–20.
J.-P. Fouque, G. Papanicolaou, K. Ronnie Sircar, Derivatives in Financial Markets with Stochastic Volatility, Cambridge University Press; 1st edition (July 3, 2000).
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  • Home
  • Courses
  • Timetable
  • Opportunities
  • Applying
  • Contact
  • Internship
  • Optimal transport
  • Algorithmic game theory
  • Neural network