Variance Optimal Hedging for discrete time processes with independent increments. Application to Electricity Markets
january, 2014
Publication type:
Paper in peer-reviewed journals
Journal:
Journal of Computational Finance., vol. 17 (2), pp. 71-111
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Keywords :
Variance-optimal hedging; Föllmer-Schweizer decomposition; Lévy process; Cumulative generating function; Characteristic function; Normal Inverse Gaussian distribution; Electricity markets; Incomplete
Markets; Processes with independent increments; trading dates optimization.
Abstract:
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 Föllmer-Schweizer decomposition for solving the mean-variance hedging problem. In particular, we establish that decomposition explicitly, 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.
BibTeX:
@article{Gou-Oud-Rus-2014-1, author={Stéphane Goutte and Nadia Oudjane and Francesco Russo }, title={Variance Optimal Hedging for discrete time processes with independent increments. Application to Electricity Markets }, doi={10.21314/JCF.2013.261 }, journal={Journal of Computational Finance. }, year={2014 }, month={1}, volume={17 (2) }, pages={71--111}, }