IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v166y2022ics1366554522002587.html
   My bibliography  Save this article

A hedging policy for seaborne forward freight markets based on probabilistic forecasts

Author

Listed:
  • Sel, Burakhan
  • Minner, Stefan

Abstract

Rate volatilities in seaborne freight markets lead charterers and ship owners to use financial agreements such as Forward Freight Agreements (FFA) for fixing freight rates in advance. The use of FFAs requires effective hedging policies since fixing freight rates in advance might cause both benefits and opportunity costs depending on future rate changes. We propose a data-driven hedging policy prescribing purchasing decisions for FFAs based on comparisons of FFA rates with future spot rate forecasts. The proposed approach is based on probabilistic forecasts instead of point forecasts because the most accurate forecasts in terms of predictive errors do not necessarily lead to the best decisions. We adjust spot rate forecasts by selecting percentiles that result in minimum prescriptive errors (i.e., cost) in cross-validation. Experiments on synthetic data show that the probabilistic forecast-based hedging policy outperforms the point forecast-based policies and benchmark policies, including data-driven policies from the literature. Experiments on Baltic Exchange data from 15 dry bulk and tanker routes confirm the performance of the proposed policy. Compared to two different point forecast-based policies defined in this study, the proposed approach achieves on average 3.31% and 3.02% total procurement cost reduction per route in 15 routes for four years testing period. It results in from 0.67% to 4.79% cost reductions against the benchmark policies.

Suggested Citation

  • Sel, Burakhan & Minner, Stefan, 2022. "A hedging policy for seaborne forward freight markets based on probabilistic forecasts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
  • Handle: RePEc:eee:transe:v:166:y:2022:i:c:s1366554522002587
    DOI: 10.1016/j.tre.2022.102881
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554522002587
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2022.102881?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wolfgang Bessler & Wolfgang Drobetz & Jörg Seidel, 2008. "Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets," Journal of Asset Management, Palgrave Macmillan, vol. 9(2), pages 102-120, July.
    2. Wang, Yi & Gan, Dahua & Sun, Mingyang & Zhang, Ning & Lu, Zongxiang & Kang, Chongqing, 2019. "Probabilistic individual load forecasting using pinball loss guided LSTM," Applied Energy, Elsevier, vol. 235(C), pages 10-20.
    3. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    4. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    5. Sun, Xiaolin & Haralambides, Hercules & Liu, Hailong, 2019. "Dynamic spillover effects among derivative markets in tanker shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 384-409.
    6. Jingbo Yin & Jinhao Shi, 2018. "Seasonality patterns in the container shipping freight rate market," Maritime Policy & Management, Taylor & Francis Journals, vol. 45(2), pages 159-173, February.
    7. Fotis Papailias & Dimitrios D. Thomakos & Jiadong Liu, 2017. "The Baltic Dry Index: cyclicalities, forecasting and hedging strategies," Empirical Economics, Springer, vol. 52(1), pages 255-282, February.
    8. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    9. Lim, Kian Guan & Nomikos, Nikos K. & Yap, Nelson, 2019. "Understanding the fundamentals of freight markets volatility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 1-15.
    10. Basil A. Kalymon, 1971. "Stochastic Prices in a Single-Item Inventory Purchasing Model," Operations Research, INFORMS, vol. 19(6), pages 1434-1458, October.
    11. Angelopoulos, Jason & Sahoo, Satya & Visvikis, Ilias D., 2020. "Commodity and transportation economic market interactions revisited: New evidence from a dynamic factor model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    12. Claudio Ferrari & Francesco Parola & Alessio Tei, 2015. "Determinants of slow steaming and implications on service patterns," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(7), pages 636-652, October.
    13. Nicola Secomandi & Guoming Lai & François Margot & Alan Scheller-Wolf & Duane J. Seppi, 2015. "Merchant Commodity Storage and Term-Structure Model Error," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 302-320, July.
    14. Alizadeh, Amir H., 2013. "Trading volume and volatility in the shipping forward freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 250-265.
    15. Gu, Yimiao & Chen, Zhenxi & Lien, Donald & Luo, Meifeng, 2020. "Quantile hedge ratio for forward freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    16. Johannes Leitner & Robert Schmidt, 2006. "A systematic comparison of professional exchange rate forecasts with the judgemental forecasts of novices," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(1), pages 87-102, February.
    17. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2019. "Commodity Price Forecasts, Futures Prices, and Pricing Models," Management Science, INFORMS, vol. 65(9), pages 4141-4155, September.
    18. Ziaul Haque Munim & Mariia Dushenko & Veronica Jaramillo Jimenez & Mohammad Hassan Shakil & Marius Imset, 2020. "Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(5), pages 577-597, July.
    19. Christos Katris & Manolis G. Kavussanos, 2021. "Time series forecasting methods for the Baltic dry index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1540-1565, December.
    20. Jun Li & Michael G. Parsons, 1997. "Forecasting tanker freight rate using neural networks," Maritime Policy & Management, Taylor & Francis Journals, vol. 24(1), pages 9-30, January.
    21. Qianqian Han & Bo Yan & Guobao Ning & B. Yu, 2014. "Forecasting Dry Bulk Freight Index with Improved SVM," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-12, June.
    22. Batchelor, Roy & Alizadeh, Amir & Visvikis, Ilias, 2007. "Forecasting spot and forward prices in the international freight market," International Journal of Forecasting, Elsevier, vol. 23(1), pages 101-114.
    23. Kavussanos, Manolis G. & Alizadeh-M, Amir H., 2002. "Seasonality patterns in tanker spot freight rate markets," Economic Modelling, Elsevier, vol. 19(5), pages 747-782, November.
    24. Manolis G. Kavussanos & Ilias D. Visvikis, 2006. "Shipping freight derivatives: a survey of recent evidence," Maritime Policy & Management, Taylor & Francis Journals, vol. 33(3), pages 233-255, July.
    25. Dimitris Bertsimas & Nathan Kallus, 2020. "From Predictive to Prescriptive Analytics," Management Science, INFORMS, vol. 66(3), pages 1025-1044, March.
    26. Gavriilidis, Konstantinos & Kambouroudis, Dimos S. & Tsakou, Katerina & Tsouknidis, Dimitris A., 2018. "Volatility forecasting across tanker freight rates: The role of oil price shocks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 376-391.
    27. Lepenioti, Katerina & Bousdekis, Alexandros & Apostolou, Dimitris & Mentzas, Gregoris, 2020. "Prescriptive analytics: Literature review and research challenges," International Journal of Information Management, Elsevier, vol. 50(C), pages 57-70.
    28. Vangelis Tsioumas & Stratos Papadimitriou, 2018. "The dynamic relationship between freight markets and commodity prices revealed," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(2), pages 267-279, June.
    29. Christian Mandl & Selvaprabu Nadarajah & Stefan Minner & Srinagesh Gavirneni, 2022. "Data‐driven storage operations: Cross‐commodity backtest and structured policies," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2438-2456, June.
    30. Jostein Tvedt, 2003. "Shipping market models and the specification of freight rate processes," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 5(4), pages 327-346, December.
    31. Kavussanos, Manolis G. & Alizadeh-M, Amir H., 2001. "Seasonality patterns in dry bulk shipping spot and time charter freight rates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(6), pages 443-467, December.
    32. Amir H. Alizadeh & Nikos K. Nomikos, 2009. "Shipping Derivatives and Risk Management," Palgrave Macmillan Books, Palgrave Macmillan, number 978-0-230-23580-9, December.
    33. Selvaprabu Nadarajah & François Margot & Nicola Secomandi, 2015. "Relaxations of Approximate Linear Programs for the Real Option Management of Commodity Storage," Management Science, INFORMS, vol. 61(12), pages 3054-3076, December.
    34. Nicola Secomandi & Sunder Kekre, 2014. "Optimal Energy Procurement in Spot and Forward Markets," Manufacturing & Service Operations Management, INFORMS, vol. 16(2), pages 270-282, May.
    35. Adland, Roar & Cullinane, Kevin, 2006. "The non-linear dynamics of spot freight rates in tanker markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(3), pages 211-224, May.
    36. Nagy, Gábor I. & Barta, Gergő & Kazi, Sándor & Borbély, Gyula & Simon, Gábor, 2016. "GEFCom2014: Probabilistic solar and wind power forecasting using a generalized additive tree ensemble approach," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1087-1093.
    37. Wolfgang Bessler & Wolfgang Drobetz & Jorg Seidel, 2008. "Erratum: Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets," Journal of Asset Management, Palgrave Macmillan, vol. 9(3), pages 254-254, September.
    38. N.D. Geomelos & E. Xideas, 2014. "Forecasting spot prices in bulk shipping using multivariate and univariate models," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-37, December.
    39. Bai, Xiwen & Cheng, Liangqi & Iris, Çağatay, 2022. "Data-driven financial and operational risk management: Empirical evidence from the global tramp shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    40. Jiao Zhang & Qingcheng Zeng & Xiaofeng Zhao, 2014. "Forecasting spot freight rates based on forward freight agreement and time charter contract," Applied Economics, Taylor & Francis Journals, vol. 46(29), pages 3639-3648, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuting Gong & Xueqin Wang & Mo Zhu & Ying‐En Ge & Wenming Shi, 2023. "Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 69-89, January.
    2. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    3. Sun, Xiaolin & Haralambides, Hercules & Liu, Hailong, 2019. "Dynamic spillover effects among derivative markets in tanker shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 384-409.
    4. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    5. Alizadeh, Amir H. & Huang, Chih-Yueh & van Dellen, Stefan, 2015. "A regime switching approach for hedging tanker shipping freight rates," Energy Economics, Elsevier, vol. 49(C), pages 44-59.
    6. Wolfgang Drobetz & Tim Richter & Martin Wambach, 2012. "Dynamics of time-varying volatility in the dry bulk and tanker freight markets," Applied Financial Economics, Taylor & Francis Journals, vol. 22(16), pages 1367-1384, August.
    7. Yimiao Gu & Zhenxi Chen & Qingyang Gu, 2022. "Determinants and international influences of the Chinese freight market," Empirical Economics, Springer, vol. 62(5), pages 2601-2618, May.
    8. Adewuyi, Adeolu O. & Adeleke, Musefiu A. & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel, 2023. "Dynamic linkages between shipping and commodity markets: Evidence from a novel asymmetric time-frequency method," Resources Policy, Elsevier, vol. 83(C).
    9. Adland, Roar & Alizadeh, Amir H., 2018. "Explaining price differences between physical and derivative freight contracts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 20-33.
    10. Abouarghoub, Wessam & Nomikos, Nikos K. & Petropoulos, Fotios, 2018. "On reconciling macro and micro energy transport forecasts for strategic decision making in the tanker industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 225-238.
    11. Yu, Fangping & Xiang, Zhiyuan & Wang, Xuanhe & Yang, Mo & Kuang, Haibo, 2023. "An innovative tool for cost control under fragmented scenarios: The container freight index microinsurance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    12. Bai, Xiwen & Lam, Jasmine Siu Lee & Jakher, Astha, 2021. "Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    13. Ioannis Karaoulanis & Theodore Pelagidis, 2021. "Panamax markets behaviour: explaining volatility and expectations," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-24, December.
    14. Fotis Papailias & Dimitrios D. Thomakos & Jiadong Liu, 2017. "The Baltic Dry Index: cyclicalities, forecasting and hedging strategies," Empirical Economics, Springer, vol. 52(1), pages 255-282, February.
    15. Jason Angelopoulos, 2017. "Time–frequency analysis of the Baltic Dry Index," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(2), pages 211-233, June.
    16. Pouliasis, Panos K. & Papapostolou, Nikos C. & Kyriakou, Ioannis & Visvikis, Ilias D., 2018. "Shipping equity risk behavior and portfolio management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 178-200.
    17. Christos Katris & Manolis G. Kavussanos, 2021. "Time series forecasting methods for the Baltic dry index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1540-1565, December.
    18. Alizadeh, Amir H. & Kappou, Konstantina & Tsouknidis, Dimitris & Visvikis, Ilias, 2015. "Liquidity effects and FFA returns in the international shipping derivatives market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 58-75.
    19. Amir Alizadeh & Wayne Talley, 2011. "Microeconomic determinants of dry bulk shipping freight rates and contract times," Transportation, Springer, vol. 38(3), pages 561-579, May.
    20. Yang, Jialin & Ge, Ying-En & Li, Kevin X., 2022. "Measuring volatility spillover effects in dry bulk shipping market," Transport Policy, Elsevier, vol. 125(C), pages 37-47.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:166:y:2022:i:c:s1366554522002587. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.