Improving forecasting via multiple temporal aggregation

Petropoulos, Fotios and Kourentzes, Nikos (2014) Improving forecasting via multiple temporal aggregation. Foresight: The International Journal of Applied Forecasting, 2014 (34). pp. 12-17.

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Abstract

In most business forecasting applications, the decision-making need we have directs the frequency of the data we collect (monthly, weekly, etc.) and use for forecasting. In this article we introduce an approach that combines forecasts generated by modeling the different frequencies (levels of temporal aggregation). Their technique augments our information about the data used for forecasting and, as such, can result in more accurate forecasts. It also automatically reconciles the forecasts at different levels.

Item Type:
Journal Article
Journal or Publication Title:
Foresight: The International Journal of Applied Forecasting
ID Code:
70550
Deposited By:
Deposited On:
27 Aug 2014 08:04
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 01:54