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On the Structure of a Swing Contract's Optimal Value and Optimal Strategy

Part of: Operations research and management science

Published online by Cambridge University Press:  14 July 2016

Sheldon M. Ross  and
Zegang Zhu
Sheldon M. Ross*
Affiliation:
University of Southern California
Zegang Zhu*
Affiliation:
University of California, Berkeley
*
∗Postal address: Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, 3715 McClintock Avenue, GER 240, Los Angeles, CA 90089-0193, USA. Email address: [email protected]
∗∗Current address: 100 W 93rd St., Apt. 27E, New York, NY 10025, USA. Email address: [email protected]
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Abstract

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Consider a sales contract, called a swing contract, between a seller and a buyer concerning some underlying commodity, with the contract specifying that during some future time interval the buyer will purchase an amount of the commodity between some specified minimum and maximum values. The purchase price and capacity at each time point is also prespecified in the contract. Assuming a random market price process and ignoring the possibility of storage, we look for the maximal expected net gain for the buyer of such a contract, and the strategy that achieves this maximal expected net gain. We study the effects that various contract constraints and market price processes have on the optimal strategy and on the contract value. We show how we can reduce the general swing contract to a multiple exercising of American (Bermudan) style options. Also, in important special cases, we give explicit expressions for the optimal contract value function and the optimal strategy.

Keywords

Swing contractAmerican call optionoptimal strategysupermodularsubmodular

MSC classification

Secondary: 90B50: Management decision making, including multiple objectives 90C40: Markov and semi-Markov decision processes
Type
Research Article
Information
Journal of Applied Probability , Volume 45 , Issue 1 , March 2008 , pp. 1 - 15
Copyright
Copyright © Applied Probability Trust 2008 

Footnotes

Supported by the National Science Foundation, grant ECS-0224779, the University of California, and by a grant from OpenLink Financial Inc.

Supported by the National Science Foundation, grant ECS-0224779, and the University of California.

References

[1] Ali, A. L., Mohamadreza, S. and Antony, W. (2001). A discrete valuation of swing options. Canad. Appl. Math. Quat. 9, 35–73.Google Scholar
[2] Barbieri, A. and Garman, M. B. (1996). Putting a price on swings. Energy Power Risk Manag. 1.Google Scholar
[3] Barbieri, A. and Garman, M. B. (1996). Understanding the valuation of swing contract. Energy Power Risk Manag. 1.Google Scholar
[4] Carmona, R. and Touzi, N. (2003). Optimal multiple stopping and valuation of swing options. Tech. Rep. Available at http://www.cmap.polytechnique.fr/∼touzi/.Google Scholar
[5] Carmona, R. and Dayanic, S. (2003). Optimal multiple stopping of linear diffusions and swing options. Tech. Rep. Available at http://www.princeton.edu/∼sdayanik/.Google Scholar
[6] Deng, S. (1999). Stochastic models of energy commodity prices: mean reversion with Jumps and spikes. Working paper, Georgia Institute of Technology. Available at http://www.ucei.berkeley.edu/.Google Scholar
[7] Jaillet, P., Ronn, E. and Tompaidis, S. (2003). Valuation of commodity-based swing options. Manag. Sci. 50, 909–921.CrossRefGoogle Scholar
[8] Keppo, J. (2004). Pricing of electricity swing options. J. Derivatives 11, 26–43.CrossRefGoogle Scholar
[9] Pilipovic, D. and Wengler, J. (1998). Getting into the swing. Energy Power Risk Manag. 2.Google Scholar
[10] Ross, S. M. (1983). Introduction to Stochastic Dynamic Programming. Academic Press, Boston, MA.Google Scholar
[11] Ross, S. M. and Zhu, Z. (2005). Computing the value of swing contract. Tech. Rep. Google Scholar
[12] Schwartz, E. (1997). The stochastic behavior of commodity prices: implications for valuation and hedging. J. Finance 52, 923–973.Google Scholar
[13] Schwartz, E. and James, S. (2000). Short-term variation and long-term dynamics of commodity prices. Manag. Sci. 46, 893–911.Google Scholar
[14] Shaked, M. and Shanthikumar, J. G. (1994). Stochastic Orders and Their Applications. Academic Press, Boston, MA.Google Scholar