Valuation of Storage at a Liquefied Natural Gas Terminal

Guoming Lai (), Mulan X. Wang (), Sunder Kekre (), Alan Scheller-Wolf () and Nicola Secomandi ()
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Guoming Lai: McCombs School of Business, University of Texas at Austin, Austin, Texas 78712
Mulan X. Wang: DTE Energy Trading, Ann Arbor, Michigan 48104
Sunder Kekre: Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Alan Scheller-Wolf: Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Nicola Secomandi: Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213

Operations Research, 2011, vol. 59, issue 3, 602-616

Abstract: The valuation of the real option to store liquefied natural gas (LNG) at the downstream terminal of an LNG value chain is an important problem in practice. Because the exact valuation of this real option is computationally intractable, we develop a novel and tractable heuristic model for its strategic valuation that integrates models of LNG shipping, natural gas price evolution, and inventory control and sale into the wholesale natural gas market. We incorporate real and estimated data to quantify the value of this real option and its dependence on the throughput of an LNG chain, the type of price variability, the type of inventory control policy employed, and the level of stochastic variability in both the shipping model and the natural gas price model used. In addition, we develop an imperfect information dual upper bound to assess the effectiveness of our heuristic and find that our method is near optimal. Our approach also has potential relevance to value the real option to store other commodities in facilities located downstream from a commodity production or transportation stage, such as petroleum and agricultural products, chemicals, and metals, or the real option to store the input used in the production of a commodity such as electricity.

Keywords: finance; asset pricing; real options; storage valuation; dynamic programming; heuristics; Markov; upper bounds; industries; petroleum/natural gas (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (26)

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