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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.

 News

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

Abbaye des Vaux de Cernay – 16-17 juin 2016

L’objectif de ces deux journées était de faire le point sur les travaux conduits au sein de l’IdR FiME, les résultats déjà obtenus et les perspectives de développement de ces travaux. Les travaux était présentés au travers d’ateliers co-animés par les ingénieurs chercheurs d’EDF R&D et les chercheurs académiques, et de quelques exposés magistraux (PL Lions, B Villeneuve, I Ekeland).

 Last publications

27
Sep
2016

A Non-Intrusive Stratified Resampler for Regression Monte Carlo: Application to Solving Non-Linear Equations

EMMANUEL GOBET, GANG LIU, AND JORGE P. ZUBELLI Abstract. Our goal is to solve certain dynamic programming equations associated to a given Markov chain X, using a regression-based Monte Carlo algorithm. More speci cally, we assume that the model for X is not known in full detail and only a root sample X1; : : : ;XM...
27
Sep
2016

Pricing American options using martingale bases

J. Lelong In this work, we propose an algorithm to price American options by directly solving the dual minimization problem introduced by Rogers . Our approach relies on approximating the set of uniformly square integrable martingales by a finite dimensional Wiener chaos expansion. Then, we use a sample average approximation technique to efficiently solve...
22
Sep
2016

Volatility in electricity derivative markets: the Samuelson effect revisited

Edouard Jaeck, Delphine Lautier This article proposes an empirical study of the Samuelson effect in electricity markets. Our motivations are twofold. First, although the literature largely assesses the decreasing pattern in the volatilities along the price curve in commodity markets, it has not extensively tested the presence of such a dynamic feature in electricity...