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Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series

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  • Gur Ali, Ozden
  • Pinar, Efe

Abstract

Multi-period sales forecasts are important inputs for operations at retail chains with hundreds of stores, and many different formats, customer segments and categories. In addition to the effects of seasonality, holidays and marketing, correlated random disturbances also affect sales across stores that share common characteristics.

Suggested Citation

  • Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
    • Handle: RePEc:eee:intfor:v:32:y:2016:i:2:p:502-517
    DOI: 10.1016/j.ijforecast.2015.03.011
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    Cited by:

    1. Elisabeth Obermair & Andreas Holzapfel & Heinrich Kuhn, 2023. "Operational planning for public holidays in grocery retailing - managing the grocery retail rush," Operations Management Research, Springer, vol. 16(2), pages 931-948, June.
    2. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    3. Gür Ali, Özden & Gürlek, Ragıp, 2020. "Automatic Interpretable Retail forecasting with promotional scenarios," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1389-1406.
    4. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
    5. Li, Chen, 2020. "Designing a short-term load forecasting model in the urban smart grid system," Applied Energy, Elsevier, vol. 266(C).

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