Abstract
In this paper, we derive the price of the forward freight contract using spot-forward relationship framework. We base our pricing on six different stochastic models which can capture many stylized facts of spot freight rates such as heavy-tailed logreturns, time-varying volatility and mean reversion. The models are analytically tractable which allows for pricing of forwards. We also examine the shape of forward curve for all continuous-time forward pricing formulas and find various shapes being the combination of fixed and stochastically dependent terms. Finally, this paper discusses the effect of different time to delivery and the maturity effect to the forward curve.
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References
Barndorff-Nielsen, O.E.: Processes of normal inverse Gaussian type. Financ. Stoch. 2(1), 41–68 (1998)
Barndorff-Nielsen, O.E., Shephard, N.: Non-Gaussian Ornstein–Uhlenbeck-based models and some of their uses in financial economics. J. R. Stat. Soc. B 63(Part 2), 167–241 (2001)
Barndorff-Nielsen, O.E., Shiryaev, A.: Change of Time and Change of Measure. World Scientific, Singapore (2010)
Benth, F.E., Šaltytė, Benth J.: The normal inverse Gaussian distribution and spot price modelling in energy markets. Int. J. Theor. Appl. Financ. 7(2), 177–192 (2004)
Benth, F.E., Šaltytė, Benth J., Koekebakker, S.: Stochastic Modelling of Electricity and Related Markets. World Scientific, Singapore (2008)
Benth, F.E.: The stochastic volatility model of Barndorff-Nielsen and Shephard in commodity markets. Math. Financ. 21(4), 595–625 (2011)
Benth, F.E., Sgarra, C.: The risk premium and the Esscher transform in power markets. Stoch. Anal. Appl. 30, 20–43 (2012)
Benth, F.E., Koekebakker, S., Taib, C.M.I.C.: Stochastic dynamical modelling of spot freight rates. IMA J. Manag. Math. (2014). doi:10.1093/imaman/dpu001
Borovkova, S., Geman, H.: Seasonal and stochastic effects in commodity forward curves. Rev. Deriv. Res. 9, 167–186 (2006)
Brockwell, P.J.: Lévy-driven CARMA process. Ann. Inst. Stat. Math. 53(1), 113–124 (2001)
Esscher, F.: On the probability function in the collective theory of risk. Skand. Aktuarietidskr. 15, 175–195 (1932)
Gerber, H.U., Shiu, E.S.W.: Option pricing by Esscher transforms. Trans. Soc. Actuar. 46, 99–191 (1994). (with discussion)
Hardle, W.K., Lopez Cabrera, B.: The implied market price of weather risk. Appl. Math. Financ. 19(1), 59–95 (2009)
Kavussanov, M., Alizadeh, M.A.H.: Seasonality patterns in tanker spot freight rate markets. Econ. Model. 19, 747–782 (2002)
Kavussanov, M., Nomikos, N.: The forward pricing function of the shipping freight futures market. J. Futur. Mark. 19, 353–376 (1999)
Kavussanov, M., Nomikos, N.: Futures hedging when the structure of the underlying asset changes: the case of the BIFFEX contract. J. Futur. Mark. 20, 776–801 (2000)
Koekebakker, S., Ådland, R.O.: Modelling forward freight rate dynamics-empirical evidence from time charter rates. Marit. Policy Manag. 31(4), 319–335 (2004)
Prokopczuk, M.: Pricing and hedging in the freight futures market. J. Futur. Mark. 31, 440–464 (2011)
Schwartz, E.S.: The stochastic behaviour of commodity prices: implications for valuation and hedging. J. Financ. 52(3), 923–973 (1997)
Zhang, S., Zhang, X.: Exact simulation of IG-OU processes. Methodol. Comput. Appl. Probab. 10, 337–355 (2008)
Acknowledgments
Author acknowledges financial support from the project “Managing Weather Risk in Electricity Markets (MAWREM)” funded by the Norwegian Research Council under Grant RENERGI 216096. Fred Espen Benth is thanked for his suggestions and valuable comments in improving the paper.
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Taib, C.M.I. Forward pricing in the shipping freight market. Japan J. Indust. Appl. Math. 33, 3–23 (2016). https://doi.org/10.1007/s13160-015-0204-6
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DOI: https://doi.org/10.1007/s13160-015-0204-6
Keywords
- Freight market
- Forward price
- Lévy processes
- Normal inverse Gaussian distribution
- Stochastic volatility
- Autoregressive moving average