Supply Chain Management and Economic Valuation of Real Options in the Natural Gas and Liquefied Natural Gas Industry

My dissertation concentrates on several aspects of supply chain management and economic valuation of real options in the natural gas and liquefied natural gas (LNG) industry, including gas pipeline transportation, ocean LNG shipping logistics, and downstream storage. Chapter 1 briefly introduces the natural gas and LNG industries, and the topics studied in this thesis. Chapter 2 studies how to value U.S. natural gas pipeline network transport contracts as real options. It is common for natural gas shippers to value and manage contracts by simple adaptations of financial spread option formulas that do not fully account for the implications of the capacity limits and the network structure that distinguish these contracts. In contrast, we show that these operational features can be fully captured and integrated with financial considerations in a fairly easy and managerially significant manner by a model that combines linear programming and simulation. We derive pathwise estimators for the so called deltas and structurally characterize them. We interpret them in a novel fashion as discounted expectations, under a specific weighing distribution, of the amounts of natural gas to be procured/marketed when optimally using pipeline capacity. Based on the actual prices of traded natural gas futures and basis swaps, we show that an enhanced version of the common approach employed in practice can significantly underestimate the true value of natural gas pipeline network capacity. Our model also exhibits promising financial (delta) hedging performance. Thus, this model emerges as an easy to use and useful tool that natural gas shippers can employ to support their valuation and delta hedging decisions concerning natural gas pipeline network transport capacity contracts. Moreover, the insights that follow from our data analysis have broader significance and implications in terms of the management of real options beyond our specific application. Motivated by current developments in the LNG industry, Chapter 3 studies the operations of LNG supply chains facing both supply and price risk. To model the supply uncertainty, we employ a closed-queuing-network (CQN) model to represent upstream LNG production and shipping, via special ocean-going tankers, to a downstream re-gasification facility in the U.S, which sells natural gas into the wholesale spot market. The CQN shipping model analytically generates the unloaded amount probability distribution. Price uncertainty is captured by the spot price, which experiences both volatility and significant seasonality, i.e., higher prices in winter. We use a trinomial lattice to model the price uncertainty, and calibrate to the extended forward curves. Taking the outputs from the CQN model and the spot price model as stochastic inputs, we formulate a real option inventory-release model to study the benefit