IDEAS home Printed from https://ideas.repec.org/a/cmc/annals/v20y2013i2p205-208.html
   My bibliography  Save this article

Application of autoregressive models for forecasting the Baltic Exchange Dry Index

Author

Listed:
  • Batrinca Ghiorghe

    (Constanta Maritime University Romania)

  • Cojanu Gianina

    (Constanta Maritime University Romania)

  • Surugiu Ioana

    (Constanta Maritime University Romania)

Abstract

The shipping industry has been growing rapidly from year to year and until not too long ago, shipping was both the greatest beneficiary and hammering pulse of globalization. But now the global economic and financial crisis has multiplied the problems of shipping industry, generating a high volatility of prices. In this context, it becomes imperious to analyze and estimate the dynamics of various indices that could be useful to capture market volatility in real time. In this respect, the Baltic Dry Index is considered to be a leading indicator of economic activity reflecting global demand for raw materials, representing a reliable and independent source of information

Suggested Citation

  • Batrinca Ghiorghe & Cojanu Gianina & Surugiu Ioana, 2013. "Application of autoregressive models for forecasting the Baltic Exchange Dry Index," Constanta Maritime University Annals, Constanta Maritime University, vol. 20(2), pages 205-208.
  • Handle: RePEc:cmc:annals:v:20:y:2013:i:2:p:205-208
    as

    Download full text from publisher

    File URL: http://cmu-edu.eu/RePEc/cmc/annals/205-v20.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicholas Apergis & James E. Payne, 2013. "New Evidence on the Information and Predictive Content of the Baltic Dry Index," IJFS, MDPI, vol. 1(3), pages 1-19, July.
    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. Aurelia Patrascu & Radu-Serban Zaharia, 2016. "Analysis On The Evolution Of Insurance Systems In Romania - The Past Five Years," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 208-213, August.

    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. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    2. Sheng, Xin & Kim, Won Joong & Gupta, Rangan & Ji, Qiang, 2023. "The impacts of oil price volatility on financial stress: Is the COVID-19 period different?," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 520-532.
    3. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    4. Christina Anderl & Guglielmo Maria Caporale, 2023. "Shipping Cost Uncertainty, Endogenous Regime Switching and the Global Drivers of Inflation," CESifo Working Paper Series 10798, CESifo.
    5. Han, Liyan & Jin, Jiayu & Wu, Lei & Zeng, Hongchao, 2020. "The volatility linkage between energy and agricultural futures markets with external shocks," International Review of Financial Analysis, Elsevier, vol. 68(C).
    6. Alturki, Sultan & Olson, Eric, 2022. "Oil sentiment and the U.S. inflation premium," Energy Economics, Elsevier, vol. 114(C).
    7. Zhang, X. & Chen, M.Y. & Wang, M.G. & Ge, Y.E. & Stanley, H.E., 2019. "A novel hybrid approach to Baltic Dry Index forecasting based on a combined dynamic fluctuation network and artificial intelligence method," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 499-516.
    8. Han, Liyan & Wan, Li & Xu, Yang, 2020. "Can the Baltic Dry Index predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 32(C).
    9. Cai, Wenxue & Liang, Fenfen & Wan, Yanchun & Zhong, Huiling & Gu, Yimiao, 2021. "An innovative approach for constructing a shipping index based on dynamic weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    10. Graham, Michael & Peltomäki, Jarkko & Piljak, Vanja, 2016. "Global economic activity as an explicator of emerging market equity returns," Research in International Business and Finance, Elsevier, vol. 36(C), pages 424-435.
    11. Adewuyi, Adeolu O. & Adeleke, Musefiu A. & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel, 2023. "Dynamic linkages between shipping and commodity markets: Evidence from a novel asymmetric time-frequency method," Resources Policy, Elsevier, vol. 83(C).
    12. Pao-Lan Kuo & Chien-Liang Chiu & Chan-Sheng Chen & Mei-Chih Wang, 2020. "The Dynamic Relationships between the Baltic Dry Index and the BRICS Stock Markets: A Wavelet Analysis," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(3), pages 340-351, March.
    13. Arunava Bandyopadhyay & Prabina Rajib, 2023. "The asymmetric relationship between Baltic Dry Index and commodity spot prices: evidence from nonparametric causality-in-quantiles test," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 217-237, June.
    14. Husaini Said & Evangelos Giouvris, 2019. "Oil, the Baltic Dry index, market (il)liquidity and business cycles: evidence from net oil-exporting/oil-importing countries," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(4), pages 349-416, December.

    More about this item

    JEL classification:

    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

    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:cmc:annals:v:20:y:2013:i:2:p:205-208. 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: Georgiana Buzu (email available below). General contact details of provider: http://cmu-edu.eu .

    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.