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Efficient pricing of ships in the dry bulk sector of the shipping industry

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  • Manolis G. Kavussanos
  • Amir H. Alizadeh

Abstract

The aim of this paper was to investigate the validity of the Efficient Market Hypothesis in conjunction with Rational Expectations in the formation of dry bulk ship prices over the period January 1976-December 1997. Tests for market efficiency include those of orthogonality and unpredictability of excess returns on investments and tests based on the Vector Autoregressive models proposed by Campbell and Shiller. The latter methodology is extended further to a 3-variable Vector Autoregressive model, which is applicable to real assets with limited economic life. Results indicate that prices for newbuilding and second-hand vessels are not determined efficiently in the sense of Fama. Failure of the Efficient Market Hypothesis in the formation of ship prices is explained by the existence of timevarying risk premia, which relate excess returns to investors' perceptions of risk. These are modelled through the Generalized Autoregressive Conditional Heteroscedasticity in mean (GARCH-M) models. The results have important implications for shipping investment strategies, both in the newbuilding and second-hand markets.

Suggested Citation

  • Manolis G. Kavussanos & Amir H. Alizadeh, 2002. "Efficient pricing of ships in the dry bulk sector of the shipping industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 29(3), pages 303-330.
    • Handle: RePEc:taf:marpmg:v:29:y:2002:i:3:p:303-330
    DOI: 10.1080/03088830210132588
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    Citations

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    Cited by:

    1. Ying Kou & Liming Liu & Meifeng Luo, 2014. "Lead-lag relationship between new-building and second-hand ship prices," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(4), pages 303-327, July.
    2. Nektarios A. Michail & Konstantinos D. Melas, 2021. "Sentiment-Augmented Supply and Demand Equations for the Dry Bulk Shipping Market," Economies, MDPI, vol. 9(4), pages 1-14, November.
    3. Sambracos, Evangelos & Maniati, Marina, 2015. "Analysis of Financial Crisis Results on Dry Bulk Market & Financing," MPRA Paper 68601, University Library of Munich, Germany.
    4. Sambracos, Evangelos & Maniati, Marina, 2013. "Shipping Market Financing: Special Features and the Impact of Basel III," MPRA Paper 51573, University Library of Munich, Germany.
    5. Papapostolou, Nikos C. & Pouliasis, Panos K. & Kyriakou, Ioannis, 2017. "Herd behavior in the drybulk market: an empirical analysis of the decision to invest in new and retire existing fleet capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 36-51.
    6. Sun, Xiaolei & Tang, Ling & Yang, Yuying & Wu, Dengsheng & Li, Jianping, 2014. "Identifying the dynamic relationship between tanker freight rates and oil prices: In the perspective of multiscale relevance," Economic Modelling, Elsevier, vol. 42(C), pages 287-295.
    7. Alexandros M. Goulielmos, 2015. "The Multi-faceted Character of Risk in Maritime Freight Markets (Panamax) 1996-2012," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 65(1-2), pages 67-86, January-M.
    8. Kokosalakis, George & Merika, Anna & Triantafyllou, Anna, 2021. "Energy efficiency and emissions control: The response of the second-hand containerships sector," Energy Economics, Elsevier, vol. 100(C).
    9. Kou, Ying & Luo, Meifeng, 2018. "Market driven ship investment decision using the real option approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 714-729.
    10. Alizadeh, Amir H. & Nomikos, Nikos K., 2007. "Investment timing and trading strategies in the sale and purchase market for ships," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 126-143, January.
    11. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.
    12. Hercules E. Haralambides & Helen Thanopoulou, 2014. "The Economic Crisis of 2008 and World Shipping: Unheeded Warnings," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 64(2), pages 5-13, April-Jun.
    13. Engelen, Steve & Norouzzadeh, Payam & Dullaert, Wout & Rahmani, Bahareh, 2011. "Multifractal features of spot rates in the Liquid Petroleum Gas shipping market," Energy Economics, Elsevier, vol. 33(1), pages 88-98, January.
    14. Nikolaos D. Geomelos & Evangelos Xideas, 2017. "Econometric estimation of second-hand shipping markets using panel data analysis," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(1), pages 7-21, January-M.
    15. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2020. "Asset pricing with mean reversion: The case of ships," Journal of Banking & Finance, Elsevier, vol. 111(C).
    16. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2019. "Earnings yield and predictability in the dry bulk shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 140-159.
    17. Alizadeh, Amir H. & Thanopoulou, Helen & Yip, Tsz Leung, 2017. "Investors’ behavior and dynamics of ship prices: A heterogeneous agent model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 98-114.

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