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A common long-term trend for bulk shipping prices

Abstract

Previous studies regarding freight rate dynamics have explored the behaviour of freight rates and their characteristics. Specifically, many studies analyse the relation between freight rates and find that they are cointegrated. In this paper, using different factor models to jointly estimate the dynamics of freight rates, we show that freight rates are not only cointegrated but also share common long-term dynamics. This finding has crucial implications in terms of managing and hedging the risk encountered by shipping companies. For example, a simpler joint model, with a common long-term trend, may be better for characterizing freight rates than a more complicated model, with different long-term trends, that has more parameters and is more difficult to estimate.

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References

  1. Adland, R., and M. Cullinane. 2006. The non-linear dynamics of spot freight rates in tanker markets. Transportation Research Part E 42 (3): 211–224.

    Article  Google Scholar 

  2. Adland, R., and S. Koekebakker. 2004. Modelling forward freight rate dynamics—empirical evidence from time charter rates. Maritime Policy & Management 31 (4): 319–335.

    Article  Google Scholar 

  3. Adland, R., S. Koekebakker, and S. Sødal. 2006. Are spot freight rates stationary? Journal of Transport Economics and Policy 40 (3): 449–472.

    Google Scholar 

  4. Adland, R., and S. Strandenesa. 2007. A discrete-time stochastic partial equilibrium model of the spot freight market. Journal of Transport Economics and Policy 41 (2): 189–218.

    Google Scholar 

  5. Alizadeh, A., and N. Kavussanos. 2001. Seasonality patterns in dry bulk shipping spot and time charter freight rates. Transportation Research Part E: Logistics and Transportation Review 37 (6): 443–467.

    Article  Google Scholar 

  6. Alizadeh, A., and N. Kavussanos. 2002. Seasonality patterns in tanker spot freight markets. Economic Modelling 19 (5): 747–782.

    Article  Google Scholar 

  7. Angelidis, T., and G. Skiadopoulos. 2008. Measuring the market risk of freight rates: A value-at-risk approach. International Journal of Theoretical and Applied Finance 11 (5): 447–469.

    Article  Google Scholar 

  8. Cortazar, G., C. Milla, and F. Severino. 2008. A multicommodity model of futures prices: Using futures prices of one commodity to estimate the stochastic process of another. The Journal of Futures Markets 28 (6): 537–560.

    Article  Google Scholar 

  9. Cullinane, M., and K. Khanna. 1999. Economies of scale in large container ships. Journal of Transport Economics and Policy 33 (2): 185–207.

    Google Scholar 

  10. Dikos, G. 2004. New building prices: Demand inelastic or perfectly competitive? Maritime Economics & Logistics 6 (4): 312–321.

    Article  Google Scholar 

  11. Dikos, G., and H.S. Marcus. 2003. The term structure of second-hand prices: A structural partial equilibrium model. Maritime Economics & Logistics 5 (3): 251–267.

    Article  Google Scholar 

  12. Harvey, A.C. 1989. Forecasting structural time series models and the Kalman filter. Cambridge: Cambridge University Press.

    Google Scholar 

  13. Hull, J. 2012. Options, futures and other derivatives, 8th ed. Upper Saddle River: Prentice Hall.

    Google Scholar 

  14. Kavussanos, M.G., and I.D. Visvikis. 2006. Derivatives and risk management in shipping. London: Witherbys Publishing Limited & Seamanship International.

    Google Scholar 

  15. Mirantes, A.G., J. Población, and G. Serna. 2012a. The stochastic seasonal behavior of natural gas prices. European Financial Management 18 (3): 410–443.

    Article  Google Scholar 

  16. Mirantes, A.G., J. Población, and G. Serna. 2012b. Analyzing the dynamics of the refining margin: Implications for valuation and hedging. Quantitative Finance 12 (12): 1839–1855.

    Article  Google Scholar 

  17. Poblacion, J. 2015. The stochastic seasonal behavior of freight rate dynamics. Maritime Economics & Logistics 17 (2): 142–162.

    Article  Google Scholar 

  18. Población, J. forthcoming. Are recent bulk shipping prices stationary? Maritime Economics & Logistics (in press).

  19. Rygaarda, J. 2009. Valuation of time charter contracts for ships. Maritime Economics & Logistics 36 (6): 525–544.

    Google Scholar 

  20. Schwartz, E.S. 1997. The stochastic behavior of commodity prices: Implication for valuation and hedging. The Journal of Finance 52 (3): 923–973.

    Article  Google Scholar 

  21. Schwartz, E.S., and J.E. Smith. 2000. Short-term variations and long-term dynamics in commodity prices. Management Science 46 (7): 893–911.

    Article  Google Scholar 

  22. Sorensen, C. 2002. Modeling seasonality in agricultural commodity futures. The Journal of Futures Markets 22 (5): 393–426.

    Article  Google Scholar 

  23. Tvedt, J. 2003. A new perspective on price dynamics of the dry bulk market. Maritime Policy & Management 30 (3): 221–230.

    Article  Google Scholar 

Download references

Acknowledgements

This paper is the sole responsibility of its authors. The views represented here do not necessarily reflect those of the Banco de España. We thank the editor and two anonymous referees for helpful comments. We also acknowledge the financial support of Junta de Castilla-La Mancha grant PEII-2014-019-P and the Ministerio de Educación grant ECO2014-59664-P.

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Correspondence to Javier Población.

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Población, J., Serna, G. A common long-term trend for bulk shipping prices. Marit Econ Logist 20, 421–432 (2018). https://doi.org/10.1057/s41278-017-0065-9

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Keywords

  • Time charter equivalent
  • World scale
  • Freight rate
  • Common long-term trend
  • Kalman filter