A global liquefied natural gas (LNG) market is quickly emerging, with several significant development projects
very recently completed or underway; these projects consist of extraction, liquefaction, shipping, regasification, and storage facilities. Exact valuation of the real option to store LNG at the downstream terminal
of an LNG value chain is computationally intractable. Thus, we develop a novel and tractable model for
the heuristic valuation of this real option. This model uses a shipping model to represent upstream LNG
production and shipping to the downstream regasification facility; a reduced form model of the evolution
of the spot price in the wholesale natural gas market where regasified LNG is sold; a stochastic dynamic
programming model to determine a policy for inventory control at the storage facility and sale into this
market; and a final Monte Carlo simulation step to estimate the value of this policy. The basestock type
structure that we prove for our model's LNG inventory release policy is central to make the final simulation
step computationally efficient; this makes our model practical. We incorporate real and estimated data to
quantify the value of the real option to store LNG at a regasification terminal, the dependence of this value
on the level of stochastic variability in the shipping model and the type of natural gas price model used, and
the relative value of this option for different parties involved in an LNG value chain. We also develop an
upper bound, based on sample path optimization, to assess the effectiveness of our heuristic and find that
our method is highly accurate. Our model has the potential to be used to value the real option to store other
commodities in storage facilities located downstream of a commodity production or transportation stage, or
the real option to store the input used in the production of a commodity.