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Investors’ behavior and dynamics of ship prices: A heterogeneous agent model

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  • Alizadeh, Amir H.
  • Thanopoulou, Helen
  • Yip, Tsz Leung

Abstract

Distinguishing investors into speculators and operators, and classifying the former group into momentum and contrarian investors, we develop a heterogeneous agent model (HAM) to examine the dynamics of price of second-hand dry bulk ships. The results suggest that momentum strategies based on short-term measures of earnings perform significantly better than the contrarian or passive (buy-and-hold) strategies. The HAM seems to capture the dynamics of vessel prices and the investors’ behavior in the market for ships very well. Finally, an increase in participation of momentum investors tends to increase price volatility, whereas higher demand from contrarian investors seems to lower price variability.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transe:v:106:y:2017:i:c:p:98-114
    DOI: 10.1016/j.tre.2017.07.012
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    Cited by:

    1. 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.
    2. Yi Zhang & Zhe Li & Yongchao Zhang, 2020. "Validation and Calibration of an Agent-Based Model: A Surrogate Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, January.
    3. Roar Adland & Haakon Ameln & Eirik A. Børnes, 2020. "Hedging ship price risk using freight derivatives in the drybulk market," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-18, December.
    4. Konstantinos D. Melas & Photis M. Panayides & Dimitris A. Tsouknidis, 2022. "Dynamic volatility spillovers and investor sentiment components across freight-shipping markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 368-394, June.
    5. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2020. "Asset pricing with mean reversion: The case of ships," Journal of Banking & Finance, Elsevier, vol. 111(C).
    6. Maitra, Debasish & Chandra, Saurabh & Dash, Saumya Ranjan, 2020. "Liner shipping industry and oil price volatility: Dynamic connectedness and portfolio diversification," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    7. 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.
    8. Görçün, Ömer Faruk, 2022. "A novel integrated MCDM framework based on Type-2 neutrosophic fuzzy sets (T2NN) for the selection of proper Second-Hand chemical tankers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).

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