Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/29896
Title: Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
Author: Lima, Susana
Gonçalves, A. Manuela
Costa, Marco
Keywords: Time series
Holt-Winter method
Forecasting
Issue Date: 2019
Publisher: AIP Publishing
Abstract: This study deals with forecasting economic time series that have strong trends and seasonal patterns. How to bestmodel and forecast these patterns has been a long-standing issue of time series analysis. In this work, we propose a Holt-WintersExponential Smoothing approach to time series forecasting in order to increase the chance of capturing different patterns in the dataand thus improve forecasting performance. Therefore, the main propose of this study is to compare the accuracy of Holt-Wintersmodels (additive and multiplicative) for forecasting and to bring new insights about the methods used via this approach. Thesemethods are chosen because of their ability to model trend and seasonal fluctuations present in economic data. The models arefitted to time series of e-commerce retail sales in Portugal. Finally, a comparison is made and discussed
Peer review: yes
URI: http://hdl.handle.net/10773/29896
DOI: 10.1063/1.5137999
Appears in Collections:ESTGA - Comunicações
GOVCOPP - Comunicações



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