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Risk control in maritime shipping investments

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  • Skålnes, Jørgen
  • Fagerholt, Kjetil
  • Pantuso, Giovanni
  • Wang, Xin

Abstract

In this paper we extend the state-of-the-art stochastic programming models for the Maritime Fleet Renewal Problem (MFRP) to explicitly limit the risk of insolvency due to negative cash flows when making maritime shipping investments. This is achieved by modeling the payment of ships in a number of periodical installments rather than in a lump sum paid upfront, representing more closely the actual cash flows for a shipping company. Based on this, we propose two alternative risk control measures, where the first imposes that the cash flow in each time period is always higher than a desired threshold, while the second limits the Conditional Value-at-Risk. We test the two models on realistic test instances based on data from a shipping company. The computational study demonstrates how the two models can be used to assess the trade-offs between risk of insolvency and expected profits in the MFRP.

Suggested Citation

  • Skålnes, Jørgen & Fagerholt, Kjetil & Pantuso, Giovanni & Wang, Xin, 2020. "Risk control in maritime shipping investments," Omega, Elsevier, vol. 96(C).
    • Handle: RePEc:eee:jomega:v:96:y:2020:i:c:s0305048318312180
    DOI: 10.1016/j.omega.2019.07.003
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    References listed on IDEAS

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    1. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship fleet deployment with container transshipment operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 470-484.
    2. Giovanni Pantuso & Kjetil Fagerholt & Stein W. Wallace, 2016. "Uncertainty in Fleet Renewal: A Case from Maritime Transportation," Transportation Science, INFORMS, vol. 50(2), pages 390-407, May.
    3. B. J. Powell & A .N. Perkins, 1997. "Fleet deployment optimization for liner shipping: an integer programming model," Maritime Policy & Management, Taylor & Francis Journals, vol. 24(2), pages 183-192, January.
    4. Kjetil Fagerholt & Trond A. V. Johnsen & Haakon Lindstad, 2009. "Fleet deployment in liner shipping: a case study," Maritime Policy & Management, Taylor & Francis Journals, vol. 36(5), pages 397-409, October.
    5. Xinsheng, Xu & Zhiqing, Meng & Rui, Shen & Min, Jiang & Ping, Ji, 2015. "Optimal decisions for the loss-averse newsvendor problem under CVaR," International Journal of Production Economics, Elsevier, vol. 164(C), pages 146-159.
    6. Mørch, Ove & Fagerholt, Kjetil & Pantuso, Giovanni & Rakke, Jørgen, 2017. "Maximizing the rate of return on the capital employed in shipping capacity renewal," Omega, Elsevier, vol. 67(C), pages 42-53.
    7. Arslan, Ayşe N. & Papageorgiou, Dimitri J., 2017. "Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 69-96.
    8. Bakkehaug, Rikard & Eidem, Eirik Stamsø & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A stochastic programming formulation for strategic fleet renewal in shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 60-76.
    9. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.
    10. Xue, Weili & Ma, Lijun & Shen, Houcai, 2015. "Optimal inventory and hedging decisions with CVaR consideration," International Journal of Production Economics, Elsevier, vol. 162(C), pages 70-82.
    11. Giovanni Pantuso & Kjetil Fagerholt & Stein W. Wallace, 2015. "Solving Hierarchical Stochastic Programs: Application to the Maritime Fleet Renewal Problem," INFORMS Journal on Computing, INFORMS, vol. 27(1), pages 89-102, February.
    12. Meng, Qiang & Wang, Shuaian, 2012. "Liner ship fleet deployment with week-dependent container shipment demand," European Journal of Operational Research, Elsevier, vol. 222(2), pages 241-252.
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