Income uncertainty and the decision to invest in bulk shipping

Published date01 June 2018
Date01 June 2018
DOI: 10.1111/eufm.12132
Income uncertainty and the decision to invest in
bulk shipping
Ioannis Kyriakou
Panos K. Pouliasis
Nikos C. Papapostolou
Nikos K. Nomikos
Cass Business School, City, University of
London, 106 Bunhill Row, London EC1Y
We develop a coherent framework for the valuation of real
assets and determination of the optimal time to invest. To
this end, we model the stochastic nature of income and
develop methodologies for valuing traded derivatives to
facilitate model calibration. A valuation paradigm for
freight-linked assets is then presented and, using a real
option approach, we demonstrate its usefulness in invest-
ment appraisal and optimal timing of entry in the shipping
industry. We find that long-run freight rate and volatility
have an impact on the decision timing and value of the
investment that diminishes with increasing vessel age. As
time to build declines, the value of the option to wait
increases implying a high opportunity cost embedded in the
investment decision due to construction lags.
contingent claims, investment, real options, shipping, uncertainty
C13, C63, G13, G31, L92
We would like to thank theManaging Editor John A. Doukas and two anonymous refereesfor their constructive comments
and suggestions. The paper in its currentform has been presented at the Finance & Stochastics seminars of the University of
Sussex, the 5th NUS Workshop on Risk & Regulation(5th Rˆ2 Workshop 2017) in Singapore, the 2nd Symposiumon
Quantitative Financeand Risk Analysis (QFRA 2016) in Rhodes, and the Spring2016 Conference of the Multinational
Finance Society in Cyprus. Earlierversions of the paper have been presented at the Annual Conference of the International
Association of Maritime Economists (IAME 2015) in Malaysia and the 1st Symposiumon Quantitative Financeand Risk
Analysis (QFRA 2015) in Santorini.We thank all participants for useful feedback. All remaining errorsare of course our own.
Eur Financ Manag. 2018;24:387417. © 2017 John Wiley & Sons, Ltd.
Investment timing and uncerta inty are issues that call for care ful consideration when commit ting to
any investment. Managers rely e xtensively on the use of traditiona l investment valuation criteria
such as the internal rate of retur n (IRR) and net present value (NPV) . These methods, although
intuitive and easy to implement ,ha ve their shortcomings as the managerial flexibility im plicit in any
investment opportunity, that is , the option to adapt investment decision s in response to uncertainty,
is not taken into account, result ing in suboptimal investment ti ming rules. As such, managers of ten
ignore or underestimate the ex tent of uncertainty and its implic ations. This can be dealt with by
treating the investment dec ision as the exercise of an optio n under uncertainty, in which c ase real
option theory provides bette r answers. In their seminal paper, B rennan and Schwartz (1985)
evaluate natural resource inve stments based on arbitrage argu ments, where uncertainty orig inates
from the output price; oper ational policy decisions, s uch as postponing productio n temporarily or
permanently, are also exam ined. Other early contribu tions on the use of real option th eory in
evaluating investment proj ects include McDonald and Sie gel (1986), Majd and Pindyck (19 87),
Dixit (1989), Triantis and Hodde r (1990), and Pindyck (1991); we refer to Dixit and Pindyck (1994)
for a comprehensive litera ture survey. Typically, the payoff of the call op tion is a convex function of
the underlying random variabl e, thus its value increases with un certainty, that is, the greater the
uncertainty the greater the va lue of the option to invest and, hence, the ince ntive to keep the option
the investment decision is affe cted by the assessment of the option to ei ther invest
immediately or wait and observ e the progress of the investment unti l market conditions improve.
Hitherto, this is an issue that has been explore d, inter alia, in different investme nt projects such as
real estate (Grenadier, 1996 ), environmental technologie s (Cortazar, Schwartz, & Salin as, 1998),
natural resources (Kellogg , 2014; Moel & Tufano, 2002; Schwartz & Smith, 2000), and infor mation
technology (Schwartz & Zozay a-Gorostiza, 2003).
This paper focuses on deep-sea shipping. This industry lends itself to this analysis as it is the
backbone of international trade 80% of global trade by volume and 70% of global trade by value
are carried by sea and handled by ports (United Nations Conference on Trade and Development
[UNCTAD], 2015) and a leading indicator of the global economy (Kilian, 2009) that has
recently attracted much interest also in the finance and economics literature (e.g., see
Kalouptsidi, 2014; Papapostolou, Nomikos, Pouliasis, & Kyriakou, 2014). Furthermore, the
valuation of vessels has been traditionally based on the price that a well-informed rational
investor would pay for the acquisition of a vessel using conventional investment criteria such as
NPV. However, this static framework is unable to capture the market dynamics and the strategic
optionalities available to shipping investors, such as the commitment of time and capital
resources to order a vessel.
The key contribution of this paper is the development of a framework for evaluating real assets
(ships in this case) and investing based on a real-option-based approach. The methodology is applied to
the drybulk sector of the shipping industry which provides an ideal framework for empirical testing as
there are numerous strategic and managerial flexibilities embedded in shipping investment and
operation decisions (Alizadeh & Nomikos, 2009). Within this framework, two innovations are
proposed. First, we derive a new, fast, and accurate analytical method for pricing traded contingent
An exception to this rule is identified in Kandel and Pearson (2002), who find that a negative relation may exist between
the value of real options and uncertainty in the case of an incremental investment in technology aimed at reducing marginal
costs of production.

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