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The Baltic Dry Index: Cyclicalities, Forecasting and Hedging Strategies

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  • Fotis Papailias

    ()
    (Queen's University Management School, UK)

  • Dimitrios D. Thomakos

    ()
    (Department of Economics, University of Peloponnese, Greece; Rimini Centre for Economic Analysis, Rimini, Italy)

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    Abstract

    The cyclical properties of the annual growth of the Baltic Dry Index (BDI) and their implications for short-to-medium term forecasting performance are investigated. We show that the BDI has a cyclical pattern which has been stable except for a period after the 2007 crisis. This pattern has implications for improved forecasting and strategic management on the future path of the BDI. To illustrate the practicality of our results, we perform an investment exercise that depends on the predicted signs. The empirical evidence supports the presence of the cyclical component and the ability of using forecast signs for improved risk management.

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    Bibliographic Info

    Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 65_13.

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    Date of creation: Dec 2013
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    Handle: RePEc:rim:rimwps:65_13

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    Keywords: Baltic Dry Index; Commodities; Concordance; Cyclical Analysis; Forecasting; Hedging; Turning Points;

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    1. Steen Koekebakker & Roar Adland & Sigbjørn Sødal, 2006. "Are Spot Freight Rates Stationary?," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 40(3), pages 449-472, September.
    2. Harding, Don, 2008. "Detecting and forecasting business cycle turning points," MPRA Paper 33583, University Library of Munich, Germany.
    3. 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.
    4. Marlow, Peter B & Gardner, Bernard, 1980. "Some Thoughts on the Dry Bulk Shipping Sector," Journal of Industrial Economics, Wiley Blackwell, vol. 29(1), pages 71-84, September.
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    7. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    8. W. Driehuis, 1970. "An econometric analysis of liner freight rates," Review of World Economics (Weltwirtschaftliches Archiv), Springer, vol. 104(1), pages 96-119, March.
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    10. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    11. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    12. 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.
    13. Lin, Faqin & Sim, Nicholas C.S., 2013. "Trade, income and the Baltic Dry Index," European Economic Review, Elsevier, vol. 59(C), pages 1-18.
    14. 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.
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