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Trading strategies in the market for tankers

Author

Listed:
  • Amir H. Alizadeh
  • Nikos K. Nomikos

Abstract

This paper introduces a new approach in timing the sale and purchase of ships in the tanker market and examines the performance of this trading strategy over the period January 1976 to September 2004. Based on the long-run cointegration relationship between earnings and price, we establish a trading model which can be used as an indicator of investment or divestment timing decisions. We also perform statistical tests using the bootstrap approach in order to discount the possibility of data snooping biases and test the robustness of our trading models. Our results indicate that trading strategies based on earning-price ratios significantly out-perform buy and hold strategies in the tanker market.

Suggested Citation

  • Amir H. Alizadeh & Nikos K. Nomikos, 2006. "Trading strategies in the market for tankers," Maritime Policy & Management, Taylor & Francis Journals, vol. 33(2), pages 119-140, May.
    • Handle: RePEc:taf:marpmg:v:33:y:2006:i:2:p:119-140
    DOI: 10.1080/03088830600612799
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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. Amir H. Alizadeh & Nikos Nomikos, 2011. "An Investigation into the Effect of Risk Management on the Profitability of Shipping Investment and Operations," Chapters, in: Kevin Cullinane (ed.), International Handbook of Maritime Economics, chapter 7, Edward Elgar Publishing.
    3. Maitra, Debasish & Rehman, Mobeen Ur & Dash, Saumya Ranjan & Kang, Sang Hoon, 2021. "Oil price volatility and the logistics industry: Dynamic connectedness with portfolio implications," Energy Economics, Elsevier, vol. 102(C).
    4. 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.
    5. 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).
    6. Nektarios A. Michail & Konstantinos D. Melas, 2019. "A cointegrating stock trading strategy: application to listed tanker shipping companies," Journal of Shipping and Trade, Springer, vol. 4(1), pages 1-10, December.
    7. Zheng, Shiyuan & Lan, Xiangang, 2016. "Multifractal analysis of spot rates in tanker markets and their comparisons with crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 547-559.
    8. 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.
    9. Mhd Ruslan, Siti Marsila & Mokhtar, Kasypi, 2021. "Stock market volatility on shipping stock prices: GARCH models approach," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    10. Sinem Celik Girgin & Thanasis Karlis & Hong-Oanh Nguyen, 2018. "A Critical Review of the Literature on Firm-Level Theories on Ship Investment," IJFS, MDPI, vol. 6(1), pages 1-19, January.

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