Time series forecasting using Holt-Winters exponential smoothing: an application to economic data
Main Author: | |
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Publication Date: | 2019 |
Other Authors: | , |
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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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 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
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 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
AIP Publishing |
publisher.none.fl_str_mv |
AIP Publishing |
dc.source.none.fl_str_mv |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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info@rcaap.pt |
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