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What can be learned from the free destination option in the LNG imbroglio?

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  • Baba, Amina
  • Creti, Anna
  • Massol, Olivier

Abstract

We examine the profitability of flexible routing by LNG cargoes for a single supplier taking into account uncertainty in the medium-term dynamics of gas markets. First, we model the trajectory of natural gas prices in Asia, Northern America, and Europe using a Threshold Vector AutoRegression representation (TVAR) in which the system's dynamics switches back and forth between high and low regimes of oil price volatility. We then use the generalized impulse response functions (GIRF) obtained from the estimated threshold model to analyze the effects of volatility shocks on the regional gas markets dynamics. Lastly, the valuation of destination flexibility in LNG supplies is conducted using a real option approach. We generate a sample of possible future regional price trajectories using Monte Carlo simulations of our empirical model and determine for each trajectory the optimal shipping decisions and their profitability. Our results portend a substantial source of profit for the industry and reveal future movements of vessels. We discuss the conditional impact of destination flexibility on the globalization of natural gas markets.

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  • Baba, Amina & Creti, Anna & Massol, Olivier, 2020. "What can be learned from the free destination option in the LNG imbroglio?," Energy Economics, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:eneeco:v:89:y:2020:i:c:s0140988320301043
    DOI: 10.1016/j.eneco.2020.104764
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    More about this item

    Keywords

    LNG arbitrage; Destination flexibility option; Volatility; TVAR; Monte Carlo simulation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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