IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast

  • Claudio Felisoni de Angelo


  • Ronaldo Zwicker


  • Nuno Manoel Martins Dias Fouto


  • Marcos Roberto Luppe


Registered author(s):

    An important economic activity in any society regards the commercialization of assets. The retail consists exactly of the link established between the industry and the final consumer. To predict the sales is essential so that one can manage in a proper way the production and commercialization processes. In the retail, this aspect is even more important. To sale means to harmonize the concerns of those producing with those who buy. Therefore, this paper is intended to exam comparatively the application of two retail sales forecast methods in the Brazilian market: the temporal series and the neural networks. The selection of those two techniques as object of that comparison was aroused by the importance those two conceptions have assumed in the literature. Although the utilization of neural networks has provided the smallest sum of the squares of the residues, one may say that the results using models of the ARIMA type have shown to be practically equivalent.

    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:
    File Function: Full text
    Download Restriction: no

    Article provided by Fucape Business School in its journal Brazilian Business Review.

    Volume (Year): 8 (2011)
    Issue (Month): 2 (April)
    Pages: 01-21

    in new window

    Handle: RePEc:bbz:fcpbbr:v:8:y:2011:i:2:p:01-21
    Contact details of provider: Postal: Fucape Business School Brazilian Business Review Av. Fernando Ferrari, 1358, Boa Vista CEP 29075-505 Vitória-ES
    Phone: +55 27 4009-4423
    Fax: +55 27 4009-4422
    Web page:

    More information through EDIRC

    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. Sniezek, Janet A., 1989. "An examination of group process in judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 5(2), pages 171-178.
    2. Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
    3. Segura, J. V. & Vercher, E., 2001. "A spreadsheet modeling approach to the Holt-Winters optimal forecasting," European Journal of Operational Research, Elsevier, vol. 131(2), pages 375-388, June.
    4. Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
    5. 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.
    6. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    7. Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    8. Ang, Soon & O'Connor, Marcus, 1991. "The effect of group interaction processes on performance in time series extrapolation," International Journal of Forecasting, Elsevier, vol. 7(2), pages 141-149, August.
    9. Brockhoff, Klaus, 1983. "Group processes for forecasting," European Journal of Operational Research, Elsevier, vol. 13(2), pages 115-127, June.
    Full references (including those not matched with items on IDEAS)

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

    When requesting a correction, please mention this item's handle: RePEc:bbz:fcpbbr:v:8:y:2011:i:2:p:01-21. 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: (Sarah Lasso)

    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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.