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Optimal Trading Policies for Wind Energy Producer

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Journal 01 Jan 2018Embargo end date: 01 Jan 2016 France Publisher:Society for Industrial & Applied Mathematics (SIAM)Journal:SIAM Journal on Financial Mathematics, volume 9, pages 315-346 (eissn: 1945-497X,

Authors: Tan, Zongjun; Tankov, Peter;

doi: 10.1137/16m1093069 , 10.48550/arxiv.1610.04458

arXiv: 1610.04458 , http://arxiv.org/abs/1610.04458

Optimal Trading Policies for Wind Energy Producer

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Abstract

We study the optimal trading policies for a wind energy producer who aims to sell the future production in the open forward, spot, intraday and adjustment markets, and who has access to imperfect dynamically updated forecasts of the future production. We construct a stochastic model for the forecast evolution and determine the optimal trading policies which are updated dynamically as new forecast information becomes available. Our results allow to quantify the expected future gain of the wind producer and to determine the economic value of the forecasts.

Country

France

Related Organizations

UNIVERSITE PARIS DESCARTES
France
French Institute for Research in Computer Science and Automation
France
Laboratoire d'informatique de Paris 6
France
Université Paris Diderot
France
Université Paris Diderot
France

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Keywords

Quantitative Finance - Trading and Market Microstructure, optimal trading policies, [ QFIN.CP ] Quantitative Finance [q-fin]/Computational Finance [q-fin.CP], [QFIN.CP] Quantitative Finance [q-fin]/Computational Finance [q-fin.CP], [QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP], Trading and Market Microstructure (q-fin.TR), FOS: Economics and business, forecasts, wind energy, stochastic control

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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%