Investment decisions under uncertainty on LNG-powered vessels for environmental compliance

Shun Chen (), Shiyuan Zheng () and Qiang Zhang ()
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Shun Chen: Shanghai Maritime University
Shiyuan Zheng: Shanghai Maritime University
Qiang Zhang: Shanghai Maritime University

Journal of Shipping and Trade, 2018, vol. 3, issue 1, 1-19

Abstract: Abstract The shipping industry is investigating alternative fuels for ships, in order to comply with stricter emission requirements implemented by International Maritime Organization (IMO). Liquefied Natural Gas (LNG) is a promising alternative since it could reduce emissions substantially and offer potential fuel cost savings. But the investment in LNG fuelled vessels is currently facing a high degree of uncertainty, such as the differential between the prices of LNG and conventional maritime fuels, the availability of LNG and the reliability of its supply chain. This paper makes an attempt to study the possibility of investing in LNG powered vessels under uncertainty. A deferral option model is proposed to quantify the value of flexibility for deferral based on multi-variables following specified stochastic processes. By exploiting the stochastic processes, it is possible to determine the value of deferral by solving a dynamic program using a least squares Monte Carlo simulation. The model is tested on an investment of a new chemical vessel with 19,000 dwt powered by LNG. Empirical analysis may suggest different investment strategies based on the probabilities of exercising an option and related option values each year. It indicates further that the attractiveness of LNG as ship fuel is dominated by a couple of parameters: difference of ship prices between a LNG powered vessel and a reference one, the price differential between LNG and conventional fuel prices, the share of the sailing time inside Emission Control Areas (ECAs), and the supply cost of LNG.

Keywords: LNG powered vessel; Environmental compliance; Deferral option model; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1186/s41072-018-0031-4

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