Finance For Energy Market Research Centre

The Finance fo Energy Market Research Centre is a joint research project between the Université Paris-Dauphine, the Centre for Research in Economics and Statistics (CREST), the Ecole Polytechnique and the R&D Division of the EDF group.

This research centre is part of  the Chair Dauphine Ecole Polytechnique EDF Credit Agricole CIB  "Finance and Sustainable Development - A Quantitative Approach". It aims to allow researchers from all academic institutions interested in working with research engineers of  EDF R&D on issues of mathematical economics and quantitative finance long-term energy sector.


New open-source stochastic optimization library

The STochastic OPTimization library (StOpt) aims at providing tools in C++ for solving some stochastic optimization problems encountered in finance or in the industry. A python binding is available for some C++ objects provided permitting to easily solve an optimization problem by regression.

Different methods are available : dynamic programming methods based on Monte Carlo  with regressions (global, local and  sparse regressors), for underlying states following;  some uncontrolled Stochastic Differential Equations  ;  Semi-Lagrangian methods for Hamilton Jacobi Bellman general equations for underlying states following some controlled  Stochastic Differential Equations  and Stochastic Dual Dynamic Programming methods to deal with stochastic stocks management problems in high dimension

 Last publications


Estimating fast mean-reverting jumps in electricity Market models - Thomas Deschatre, Olivier Féron, and Marc Hoffmann

Based on empirical evidence of fast mean-reverting spikes, we model electricity price processes as the sum of a continuous Itö semimartingale and a a mean-reverting compound Poisson process. In a first part, we investigate the estimation of the two parameters of the Poisson process from discrete observations and establish asymptotic efficiency in various asymptotic settings. In a second...

t and stable multivariate kernel density estimation by fast sum updating - N . Langrené, X. Warin

Kernel density estimation and kernel regression are powerful but computationally expensive techniques: a direct evaluation of kernel density estimates at M evaluation points given N input sample points requires a quadratic O(MN) operations, which is prohibitive for large scale problems. For this reason, approximate methods such as binning with Fast Fourier Transform or the...

Monte Carlo for high-dimensional degenerated Semi Linear and Full Non Linear PDEs - X. Warin

We extend a recently developed method to solve semi-linear PDEs to the case of a degenerated diffusion. Being a pure Monte Carlo method it does not su er from the so called curse of dimensionality and it can be used to solve problems that were out of reach so far. We give some results of...

 Next events

  1. David Martimort (TSE)

    28 September @ 14 h 00 min - 15 h 00 min
  2. Jean-Michel Lasry (Dauphine University)

    12 October @ 14 h 00 min - 15 h 00 min
  3. TBA

    9 November @ 14 h 00 min - 15 h 00 min
  4. David Benatia (CREST-ENSAE)

    23 November @ 14 h 00 min - 15 h 00 min
  5. TBA

    7 December @ 14 h 00 min - 15 h 00 min