Valuation of Electricity Swing Options by Bilevel Model

Valuation of Electricity Swing Options by Bilevel Model

Mingzhu Wu

School of Management, Shanghai University, Shanghai 310113, China.

International Journal of Industrial and Business Management

Since the electric power cannot be stored for long time, the spot prices of electricity are extremely volatile. In order to control risks, it is necessary to introduce financial derivatives into electricity markets. This paper mainly studies the pricing of electricity swing options, which are widely applied in financial markets for electricity. Through finite difference and discretization of transaction time and price, the issue of swing option pricing is transformed to a linear complementary problem. At the same time, the optimization model is established by combining optimal behaviors of swing option buyers. Finally, through the actual data of electricity futures, above model and algorithm are used to simulate the pricing of swing options.

Keywords: Swing options; Electricity market; Complementary model.

Free Full-text PDF

How to cite this article:
Mingzhu Wu.Valuation of Electricity Swing Options by Bilevel Model. International Journal of Industrial and Business Management, 2018; 2:8. DOI:10.28933/ijibm-2018-11-0808


1. Eydeland A, Geman H. Some fundamentals of electricity derivatives [J]. Automatica, 1998, 30(3): 244–256.
2. Davison M, Anderson L. Approximate recursive valuation of electricity swing options [J]. European Journal of Operational Research, 2003, 17(3): 83–92.
3. Thompson A. Valuation of path-dependent contingent claims with multiple exercise decisions over time: The case of take-or-pay [J]. Journal of Financial and Quantitative Analysis, 1995, 30(2): 271–293.
4. Carmona R,Touzi N, Optimal multiple stopping and valuation of swing options [J]. Mathematical Finance, 2008, 18(2): 239–268.
5. Lari-Lavasanni A, Simchi M. A discrete valuation of swing options [J]. Canadian Applied Mathematics Quarterly, 2001, 9(1): 35–74.
6. Jaillet P. Valuation of commodity based swing options [J]. Management Science, 2004, 50(7): 909–921.
7. Longsta F, Schwartz, E. Valuing American options by simulation: A simple least squares approach [J]. The Review of Financial Studies, 2001, 14(4): 113–147.
8. Ibanez A. Valuation by simulation of contingent claims with multiple exercise opportunities [J]. Mathematical Finance, 2004, 14(2): 223–248.
9. Haarbrucker G, Kuhn D. Valuation of electricity swing options by multistage stochastic programming [J]. Automatica, 2009, 45(7): 889–899.
10. Georg C, Broussev N. Electricity swing options: Behavioral models and pricing [J]. European Journal of Operational Research, 2009, 19(7): 1041–1050.
11. Raimund M, Georg C. Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches [J]. European Journal of Operational Research, 2014, 27(3): 389–403.
12. Hamatani K, Fukushima M. Pricing american options with uncertain volatility through stochastic linear complementarity [J]. Computational Optimization and Applications, 2011, 50(2): 563–286.
13. Svensson O, Vorobyov S. A subexponential algorithm for a subclass of P-matrix generalized linear complementarity problems [J]. Technical Report, 2005, 16(3): 45–62.
14. Zhao J, Corless R M. Compact finite dierence method for American option pricing [J]. Journal of Computational and Applied Mathematics, 2007, 206(1): 306–321.

Terms of Use/Privacy Policy/ Disclaimer/ Other Policies:
You agree that by using our site, you have read, understood, and agreed to be bound by all of our terms of use/privacy policy/ disclaimer/ other policies (click here for details)

CC BY 4.0
This work and its PDF file(s) are licensed under a Creative Commons Attribution 4.0 International License.