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Decoupled Net Present Value—An Alternative to the Long-Term Asset Value in the Evaluation of Ship Investments?

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Operations Research Proceedings 2017

Part of the book series: Operations Research Proceedings ((ORP))

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Abstract

The aftermath of the financial crisis has threatened the stability of several financial institutions over the past years. Most heavily hit were banks with a notable exposure to ship finance, who saw the collateral value of many loans being diminished. Industry observers trace back the rare occurrence of actual defaults of ship loans to the use of the Long-Term-Asset Value (LTAV), a valuation method explicitly designed for ship investments. As the LTAV is based on a discounted cash-flow approach, it accounts for investment risks in the discount rate. Consequently, the LTAV bundles the time value of money and risk in a single value, which begs the question if this method oversimplifies the incorporation of risk in the evaluation of ship investments. In the context of infrastructure investments, the Decoupled Net Present Value (DNPV) has recently been proposed as an alternative method that addresses the problem of using risk-adjusted discount rates. It separates the time value of money from risks by quantifying risk factors individually and treating them as costs to the investment. We provide a proof-of-concept regarding the applicability of the DNPV in the context of ship investments. To this end, we develop a DNPV valuation model and instantiate a prototype in Python. We then perform a simulation study that evaluates a ship investment using both the LTAV and the DNPV. The results of our study confirm the applicability of the DNPV to ship investments and point to both its advantages and limitations compared to the LTAV.

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Correspondence to Philipp Schrader .

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Schrader, P., Piel, JH., Breitner, M.H. (2018). Decoupled Net Present Value—An Alternative to the Long-Term Asset Value in the Evaluation of Ship Investments?. In: Kliewer, N., Ehmke, J., Borndörfer, R. (eds) Operations Research Proceedings 2017. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-89920-6_37

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