Advanced Search
MyIDEAS: Login to save this article or follow this journal

Usefulness of Artificial Neural Networks for Predicting Financial and Economic Crisis

Contents:

Author Info

  • Mioara CHIRITA

    ()
    (Dunarea de Jos University of Galati, Romania)

  • Daniela SARPE

    ()
    (Dunarea de Jos University of Galati, Romania)

Registered author(s):

    Abstract

    The objective of the present study is to explore the issue of the forecasting of economic crisis using the neural network. The subject is of great importance in the economy, more so as that the most countries affected by crisis, declared on the end of 2010, the economic growth but the crisis paralyzed the financial world over the past three years. Neural network techniques have been frequently applied in order to predict problems like economic forecasting. The results show that creating a model using the neural networks might be a powerful tool and could be applied to prevent the economic crises.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.rce.feaa.ugal.ro/images/stories/RCE2011/economics/MChirita_DSarpe.pdf
    Download Restriction: no

    Bibliographic Info

    Article provided by "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration in its journal Risk in the Contemporary Economy, Proceedings Conference.

    Volume (Year): (2011)
    Issue (Month): ()
    Pages: 44-48

    as in new window
    Handle: RePEc:ddj:fserec:y:2011:p:44-48

    Contact details of provider:
    Postal: No. 59-61, Nicolae Balcescu Street, Postal Code 800008, Galati
    Phone: (0040) 336.130.242
    Fax: (0040) 336.130.242
    Email:
    Web page: http://www.feaa.ugal.ro
    More information through EDIRC

    Related research

    Keywords: economic and financial crisis; forecasting models; neural networks;

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Abdul Abiad, 2003. "Early Warning Systems," IMF Working Papers 03/32, International Monetary Fund.
    2. Kaminsky, Graciela & Lizondo, Saul & Reinhart, Carmen M., 1997. "Leading indicators of currency crises," Policy Research Working Paper Series 1852, The World Bank.
    3. Allen, Franklin & Gale, Douglas, 1999. "Bubbles, Crises, and Policy," Oxford Review of Economic Policy, Oxford University Press, vol. 15(3), pages 9-18, Autumn.
    4. Fioramanti, Marco, 2008. "Predicting sovereign debt crises using artificial neural networks: A comparative approach," Journal of Financial Stability, Elsevier, vol. 4(2), pages 149-164, June.
    5. Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 03/221, International Monetary Fund.
    6. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ddj:fserec:y:2011:p:44-48. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gianina Mihai).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.