List of courses

    1. Core modules
      • Stochastic calculus and diffusion processes (S Péché )
      • Markov Chain (M. Merle)
      • Introduction to machine learning (S. Gaiffas)
      • Data modelling: founding principles (A. Fischer & S Gribkova)
    2. Quantitative Finance Modules
      • Random modelling in finance (P. Tankov & S. Scotti)
      • Financial products (B. Bruder)
      • Energy markets (R. Aid & O. Feron)
      • Advanced interest rate modelling (Z. Grbac)
      • Model risk and model validation for pricing (P. Tankov)
    3. Data Science Modules
      • Graphical models for machine learning (F. Rossi)
      • Statistical learning (S. Clemencon and E. Chautru)
      • Projects in Data Science: CRM (K. Tribouley)
      • Methods for large/high dimensional data sets (S. Boucheron)
      • Introduction to reinforcement learning (J. Lussange)
      • Data science and statistics for industry (M. Sayed and L. Massoulard)
    4. Asset Management Modules
      • Stochastic control in finance (H. Pham)
      • Nonlinear methods in Finance (M.C. Quenez)
      • Algorithmic trading (O. Gueant)
      • Quantitative Asset management (B. Bruder)
    5. Computer Science Modules
      • C++ (O. Carton)
      • Statistical softwares (S. Souchet)
    6. Risk Management Modules 
      • Credit risk modelling (R. Rouge)
      • Risk measures and risk Management (H. Pham & A. El Alami)
      • Copulae and financial applications (J.D. Fermanian)
    7. Statistics & Finance Modules
      • Financial time series (J.M. Bardet)
      • Prediction and sequential investments (J.Y. Audibert)
      • Statistical inference for diffusion processes (A. Gloter)
      • Filtering techniques and statistical analysis applied in finance (J. Turc)
    8. Numerical & Approximation Methods Modules
      • PDE methods in finance (Y. Achdou & O. Bokanowski)
      • Monte Carlo Methods (N.Frikha)
      • Advanced probabilistic numerical methods in finance (J.-F. Chassagneux)
      • Asymptotic methods in finance (H. Pham)