IDEAS home Printed from https://ideas.repec.org/a/ovi/oviste/vxiiy2012i1p1125-1129.html
   My bibliography  Save this article

Application of Autoregressive Models for Forecasting Marine Insurance Market

Author

Listed:
  • Burcã Ana-Maria

    (Bucharest Academy of Economic Studies)

  • Bãtrînca Ghiorghe

    (Constanta Maritime University)

Abstract

The shipping industry represents an important component of the global economy. In the context of globalization the importance of marine insurance has increased more than even before. Without insurance, ship owners would be subjected to a wide range of risks that they would not be protected from. Marine insurance facilitates global trade, ensures economic property, provides peace of mind, improves quality of life and provides social benefits. Taking in consideration all these advantages, it becomes essential to analyze and forecast the evolution of the marine insurance market.

Suggested Citation

  • Burcã Ana-Maria & Bãtrînca Ghiorghe, 2013. "Application of Autoregressive Models for Forecasting Marine Insurance Market," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 1125-1129, May.
    • Handle: RePEc:ovi:oviste:v:xii:y:2012:i:1:p:1125-1129
    as

    Download full text from publisher

    File URL: http://stec.univ-ovidius.ro/html/anale/ENG/cuprins%20rezumate/volum2013p1.pdf
    Download Restriction: no
    ---><---

    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.

    More about this item

    Keywords

    marine insurance; gross written premiums; ARIMA models; forecasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    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:ovi:oviste:v:xii:y:2012:i:1:p:1125-1129. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Gheorghiu Gabriela (email available below). General contact details of provider: https://edirc.repec.org/data/feoviro.html .

    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.