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Variance Optimal Hedging for discrete time processes with independent increments. Application to Electricity Markets

Francesco Russo 1, 2, 3, Stéphane Goutte 1, Nadia Oudjane 1, 4

(13/04/2010)

We consider the discretized version of a (continuous-time) two-factor model introduced by Benth and coauthors for the electricity markets. For this model, the underlying is the exponent of a sum of independent random variables. We provide and test an algorithm, which is based on the celebrated Foellmer-Schweizer decomposition for solving the mean-variance hedging problem. In particular, we establish that decomposition explicitely, for a large class of vanilla contingent claims. Interest is devoted in the choice of rebalancing dates and its impact on the hedging error, regarding the payoff regularity and the non stationarity of the log-price process.

1 :	Laboratoire Analyse, Géométrie et Application (LAGA)
	CNRS : UMR7539 – Université Paris XIII - Paris Nord – Université Paris VIII - Vincennes Saint-Denis
2 :	Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS)
	Ecole des Ponts ParisTech
3 :	MATHFI (INRIA Rocquencourt)
	INRIA – Ecole des Ponts ParisTech – Université Paris-Est Créteil Val-de-Marne (UPEC)
4 :	EDF R&D
	EDF

Domaine

:

Mathématiques/Probabilités

Mots-clés : Variance-optimal hedging – Foellmer-Schweizer decomposition – Levy process – Cumulative generating function – Characteristic function – Normal Inverse Gaussian distribution – Electricity markets – Incomplete Markets – Processes with independent increments – Trading dates optimization

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Contributeur : Francesco Russo <>

Soumis le : Mardi 13 Avril 2010, 22:08:25

Dernière modification le : Jeudi 9 Décembre 2010, 16:07:01