Time series forecasting using Holt-Winters exponential smoothing: an application to economic data

Bibliographic Details
Main Author: Lima, Susana
Publication Date: 2019
Other Authors: Gonçalves, A. Manuela, Costa, Marco
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10773/29896
Summary: 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
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spelling Time series forecasting using Holt-Winters exponential smoothing: an application to economic dataTime seriesHolt-Winter methodForecastingThis 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 discussedAIP Publishing2020-11-25T16:05:58Z2019-01-01T00:00:00Z2019conference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10773/29896eng10.1063/1.5137999Lima, SusanaGonçalves, A. ManuelaCosta, Marcoinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-06T04:28:48Zoai:ria.ua.pt:10773/29896Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:10:00.194705Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
title Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
spellingShingle Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
Lima, Susana
Time series
Holt-Winter method
Forecasting
title_short Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
title_full Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
title_fullStr Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
title_full_unstemmed Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
title_sort Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
author Lima, Susana
author_facet Lima, Susana
Gonçalves, A. Manuela
Costa, Marco
author_role author
author2 Gonçalves, A. Manuela
Costa, Marco
author2_role author
author
dc.contributor.author.fl_str_mv Lima, Susana
Gonçalves, A. Manuela
Costa, Marco
dc.subject.por.fl_str_mv Time series
Holt-Winter method
Forecasting
topic Time series
Holt-Winter method
Forecasting
description 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
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01T00:00:00Z
2019
2020-11-25T16:05:58Z
dc.type.driver.fl_str_mv conference object
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/29896
url http://hdl.handle.net/10773/29896
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1063/1.5137999
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dc.publisher.none.fl_str_mv AIP Publishing
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