IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v19y2012i4p313-317.html
   My bibliography  Save this article

A predictive model of the freight rate of the international market in Capesize dry bulk carriers

Author

Listed:
  • Ching-Chih Chang
  • Chin-Yuan Hsieh
  • Yung-Chih Lin

Abstract

This study examines the considerable fluctuations of the world's dry bulk shipping market from November 1995 to September 2008. The major objective is to provide a forecasting model for the freight rate in relation to the second-hand ship price. The results indicate an acceptable level of prediction according to Mean Absolute Percentage Error (MAPE), with a value no more than 20%. It is anticipated that this research will prove germane to major stakeholders, including owners, charters, investors and bankers, by forecasting the freight rate and thereby expediting the decision-making process.

Suggested Citation

  • Ching-Chih Chang & Chin-Yuan Hsieh & Yung-Chih Lin, 2012. "A predictive model of the freight rate of the international market in Capesize dry bulk carriers," Applied Economics Letters, Taylor & Francis Journals, vol. 19(4), pages 313-317, March.
    • Handle: RePEc:taf:apeclt:v:19:y:2012:i:4:p:313-317
    DOI: 10.1080/13504851.2011.576998
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2011.576998
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504851.2011.576998?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. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 374-386, July.
    2. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
    3. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 396-397, July.
    4. 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.
    5. Pakko, Michael R, 2000. "The Cyclical Relationship between Output and Prices: An Analysis in the Frequency Domain," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 382-399, August.
    6. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    7. Jeff Tayman & David Swanson, 1996. "On the utility of population forecasts," Demography, Springer;Population Association of America (PAA), vol. 33(4), pages 523-528, November.
    8. den Butter, F A G & Mourik, T J, 1990. "Seasonal Adjustment Using Structural Time Series Models: An Application and Comparison with the Census X-11 Method," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 385-394, October.
    9. J. Z. Easaw & S. M. Heravi & J. C. K. Ash & D. J. Smyth, 2002. "Are Hodrick-Prescott `forecasts' rational?," Empirical Economics, Springer, vol. 27(4), pages 631-643.
    10. Casals J. & Jerez M. & Sotoca S., 2002. "An Exact Multivariate Model-Based Structural Decomposition," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 553-564, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wetzstein, Brian & Florax, Raymond & Foster, Kenneth & Binkley, James, 2021. "Transportation costs: Mississippi River barge rates," Journal of Commodity Markets, Elsevier, vol. 21(C).

    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. Eric Ghysels & Norman R. Swanson & Myles Callan, 2002. "Monetary Policy Rules with Model and Data Uncertainty," Southern Economic Journal, John Wiley & Sons, vol. 69(2), pages 239-265, October.
    2. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    3. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2005. "Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results," Econometric Institute Research Papers EI 2005-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Giancarlo Bruno & Edoardo Otranto, 2006. "The choice of time interval in seasonal adjustment: A heuristic approach," Statistical Papers, Springer, vol. 47(3), pages 393-417, June.
    5. A Matas-Mir & D R Osborn, 2003. "Seasonal Adjustment and the Detection of Business Cycle Phases," Economics Discussion Paper Series 0304, Economics, The University of Manchester.
    6. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    7. Maravall, A. & del Rio, A., 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 975-998, October.
    8. Mauricio Gallardo & Hernán Rubio, 2009. "Diagnóstico de estacionalidad con X-12-ARIMA," Economic Statistics Series 76, Central Bank of Chile.
    9. Kroes, James R. & Manikas, Andrew S. & Gattiker, Thomas F., 2018. "Operational leanness and retail firm performance since 1980," International Journal of Production Economics, Elsevier, vol. 197(C), pages 262-274.
    10. Quenneville, Benoit & Ladiray, Dominique & Lefrancois, Bernard, 2003. "A note on Musgrave asymmetrical trend-cycle filters," International Journal of Forecasting, Elsevier, vol. 19(4), pages 727-734.
    11. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, vol. 68(2), pages 169-192.
    12. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    13. Hai Yue Liu & Xiao Lan Chen, 2017. "The imported price, inflation and exchange rate pass-through in China," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1279814-127, January.
    14. Carlos A. Medel, 2018. "A Comparison Between Direct and Indirect Seasonal Adjustment of the Chilean GDP 1986–2009 with X-12-ARIMA," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 47-87, April.
    15. Stefania D'Amico & Athanasios Orphanides, 2008. "Uncertainty and disagreement in economic forecasting," Finance and Economics Discussion Series 2008-56, Board of Governors of the Federal Reserve System (U.S.).
    16. Kirchner, Robert, 1999. "Auswirkungen des neuen Saisonbereinigungsverfahrens Census X-12-ARIMA auf die aktuelle Wirtschaftsanalyse in Deutschland," Discussion Paper Series 1: Economic Studies 1999,07, Deutsche Bundesbank.
    17. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    18. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    19. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
    20. Supachoke Thawornkaiwong, 2016. "Simplified Spectral Analysis and Linear Filters for Analysis of Economic Time Series," PIER Discussion Papers 25., Puey Ungphakorn Institute for Economic Research, revised Apr 2016.

    More about this item

    Statistics

    Access and download statistics

    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:taf:apeclt:v:19:y:2012:i:4:p:313-317. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.