Forecasting: theory and practice

Fotios Petropoulos; Daniele Apiletti; Vassilios Assimakopoulos; Mohamed Zied Babai; Devon K. Barrow; Souhaib Ben Taieb; Christoph Bergmeir; Ricardo J. Bessa; Jakub Bijak; John E. Boylan; Jethro Browell; Claudio Carnevale; Jennifer L. Castle; Pasquale Cirillo; Michael P. Clements; Clara Cordeiro; Fernando Luiz Cyrino Oliveira; Shari De Baets; Alexander Dokumentov; Joanne Ellison; Piotr Fiszeder; Philip Hans Franses; David T. Frazier; Michael Gilliland; M. Sinan Gonul; Paul Goodwin; Luigi Grossi; Yael Grushka-Cockayne; Mariangela Guidolin; Massimo Guidolin; Ulrich Gunter; Xiaojia Guo; Renato Guseo; Nigel Harvey; David F. Hendry; Ross Hollyman; Tim Januschowski; Jooyoung Jeon; Victor Richmond R. Jose; Yanfei Kang; Anne B. Koehler; Stephan Kolassa; Nikolaos Kourentzes; Sonia Leva; Feng Li; Konstantia Litsiou; Spyros Makridakis; Gael M. Martin; Andrew B. Martinez; Sheik Meeran; Theodore Modis; Konstantinos Nikolopoulos; Dilek Onkal; Alessia Paccagnini; Anastasios Panagiotelis; Ioannis Panapakidis; Jose M. Pavía; Manuela Pedio; Diego J. Pedregal; Pierre Pinson; Patrícia Ramos; David E. Rapach; J. James Reade; Bahman Rostami-Tabar; Michał Rubaszek; Georgios Sermpinis; Han Lin Shang; Evangelos Spiliotis; Aris A. Syntetos; Priyanga Dilini Talagala; Thiyanga S. Talagala; Len Tashman; Dimitrios Thomakos; Thordis Thorarinsdottir; Ezio Todini; Juan Ramón Trapero Arenas; Xiaoqian Wang; Robert L. Winkler; Alisa Yusupova; Florian Ziel

doi:10.1016/j.ijforecast.2021.11.001

Forecasting: theory and practice

Fotios Petropoulos^*, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Souhaib Ben Taieb, Christoph Bergmeir, Ricardo J. Bessa, Jakub Bijak, John E. Boylan, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Joanne EllisonPiotr Fiszeder, Philip Hans Franses, David T. Frazier, Michael Gilliland, M. Sinan Gonul, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li, Konstantia Litsiou, Spyros Makridakis, Gael M. Martin, Andrew B. Martinez, Sheik Meeran, Theodore Modis, Konstantinos Nikolopoulos, Dilek Onkal, Alessia Paccagnini, Anastasios Panagiotelis, Ioannis Panapakidis, Jose M. Pavía, Manuela Pedio, Diego J. Pedregal, Pierre Pinson, Patrícia Ramos, David E. Rapach, J. James Reade, Bahman Rostami-Tabar, Michał Rubaszek, Georgios Sermpinis, Han Lin Shang, Evangelos Spiliotis, Aris A. Syntetos, Priyanga Dilini Talagala, Thiyanga S. Talagala, Len Tashman, Dimitrios Thomakos, Thordis Thorarinsdottir, Ezio Todini, Juan Ramón Trapero Arenas, Xiaoqian Wang, Robert L. Winkler, Alisa Yusupova, Florian Ziel

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

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Abstract

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts.
We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.

Original language	English
Pages (from-to)	705-871
Journal	International Journal of Forecasting
Volume	38
Issue number	3
Early online date	20 Jan 2022
DOIs	https://doi.org/10.1016/j.ijforecast.2021.11.001
Publication status	Published - 1 Jul 2022

Keywords

review
encyclopedia
methods
applications
principles
time series
prediction

Access to Document

10.1016/j.ijforecast.2021.11.001Licence: CC BY

Arxiv 2021 accepted versionAccepted author manuscript, 4.94 MBLicence: CC BY-NC-ND
Final published versionFinal published version, 3.81 MBLicence: CC BY
Advance online versionFinal published version, 3.81 MBLicence: CC BY

Cite this

Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., Browell, J., Carnevale, C., Castle, J. L., Cirillo, P., Clements, M. P., Cordeiro, C., Oliveira, F. L. C., Baets, S. D., Dokumentov, A., ... Ziel, F. (2022). Forecasting: theory and practice. International Journal of Forecasting, 38(3), 705-871. https://doi.org/10.1016/j.ijforecast.2021.11.001

@article{65e2cd52b27e45b79f15ed9a9f6d4ec5,

title = "Forecasting: theory and practice",

abstract = "Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.",

keywords = "review, encyclopedia, methods, applications, principles, time series, prediction",

author = "Fotios Petropoulos and Daniele Apiletti and Vassilios Assimakopoulos and Babai, \{Mohamed Zied\} and Barrow, \{Devon K.\} and Taieb, \{Souhaib Ben\} and Christoph Bergmeir and Bessa, \{Ricardo J.\} and Jakub Bijak and Boylan, \{John E.\} and Jethro Browell and Claudio Carnevale and Castle, \{Jennifer L.\} and Pasquale Cirillo and Clements, \{Michael P.\} and Clara Cordeiro and Oliveira, \{Fernando Luiz Cyrino\} and Baets, \{Shari De\} and Alexander Dokumentov and Joanne Ellison and Piotr Fiszeder and Franses, \{Philip Hans\} and Frazier, \{David T.\} and Michael Gilliland and Gonul, \{M. Sinan\} and Paul Goodwin and Luigi Grossi and Yael Grushka-Cockayne and Mariangela Guidolin and Massimo Guidolin and Ulrich Gunter and Xiaojia Guo and Renato Guseo and Nigel Harvey and Hendry, \{David F.\} and Ross Hollyman and Tim Januschowski and Jooyoung Jeon and Jose, \{Victor Richmond R.\} and Yanfei Kang and Koehler, \{Anne B.\} and Stephan Kolassa and Nikolaos Kourentzes and Sonia Leva and Feng Li and Konstantia Litsiou and Spyros Makridakis and Martin, \{Gael M.\} and Martinez, \{Andrew B.\} and Sheik Meeran and Theodore Modis and Konstantinos Nikolopoulos and Dilek Onkal and Alessia Paccagnini and Anastasios Panagiotelis and Ioannis Panapakidis and Pav{\'i}a, \{Jose M.\} and Manuela Pedio and Pedregal, \{Diego J.\} and Pierre Pinson and Patr{\'i}cia Ramos and Rapach, \{David E.\} and Reade, \{J. James\} and Bahman Rostami-Tabar and Micha{\l} Rubaszek and Georgios Sermpinis and Shang, \{Han Lin\} and Evangelos Spiliotis and Syntetos, \{Aris A.\} and Talagala, \{Priyanga Dilini\} and Talagala, \{Thiyanga S.\} and Len Tashman and Dimitrios Thomakos and Thordis Thorarinsdottir and Ezio Todini and Arenas, \{Juan Ram{\'o}n Trapero\} and Xiaoqian Wang and Winkler, \{Robert L.\} and Alisa Yusupova and Florian Ziel",

note = "Funding information: Jakub Bijak{\textquoteright}s work received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme, grant 870299 QuantMig: Quantifying Migration Scenarios for Better Policy. Clara Cordeiro is partially financed by national funds through FCT – Fundac¸ ˜ao para a Ciˆencia e a Tecnologia under the project UIDB/00006/2020. Fernando Luiz Cyrino Oliveira acknowledges the support of the Coordination for the Improvement of Higher Level Personnel (CAPES) – grant number 001, the Brazilian National Council for Scientific and Technological Development (CNPq) – grant number 307403/2019 0, and the Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ) – grant numbers 202.673/2018 and 211.086/2019. Shari De Baets was funded by the FWO Research Foundation Flanders. Joanne Ellison acknowledges the support of the ESRC FertilityTrends project (grant number ES/S009477/1) and the ESRC Centre for Population Change (grant number ES/R009139/1). Piotr Fiszeder was supported by the National Science Centre project number 2016/21/B/HS4/00662 entitled “Multivariate volatility models - the application of low and high prices”. David T. Frazier has been supported by Australian Research Council (ARC) Discovery Grants DP170100729 and DP200101414, and ARC Early Career Researcher Award DE200101070. Mariangela Guidolin acknowledges the support of the University of Padua, Italy, through the grant BIRD188753/18. David F. Hendry gratefully acknowledges funding from the Robertson Foundation and Nuffield College. Yanfei Kang acknowledges the support of the National Natural Science Foundation of China (number 11701022) and the National Key Research and Development Program (number 2019YFB1404600). Stephan Kolassa would like to thank Tilmann Gneiting for some very helpful tips. Gael M. Martin has been supported by Australian Research Council (ARC) Discovery Grants DP170100729 and DP200101414. Alessia Paccagnini acknowledges the research support by COST Action “Fintech and Artificial Intelligence in Finance - Towards a transparent financial industry” (FinAI) CA19130. Jose M. Pav´ıa acknowledges the support of the Spanish Ministry of Science, Innovation and Universities and the Spanish Agency of Research, co-funded with FEDER funds, grant ECO2017-87245-R, and of Conseller´ıa d{\textquoteright}Innovaci´ o, Universitats, Ci`encia i Societat Digital, Generalitat Valenciana – grant number AICO/2019/053. Diego J. Pedregal and Juan Ramon Trapero Arenas acknowledge the support of the European Regional Development Fund and Junta de Comunidades de Castilla-La Mancha (JCCM/FEDER, UE) under the 177 project SBPLY/19/180501/000151 and by the Vicerrectorado de Investigaci´on y Po ´ıtica Cient´ıfica from UCLM through the research group fund program PREDILAB; DOCM 26/02/2020 [2020-GRIN-28770]. David E. Rapach thanks Ilias Filippou and Guofu Zhou for valuable comments. J. James Reade and Han Lin Shang acknowledge Shixuan Wang for his constructive comments. Micha{\l} Rubaszek is thankful for the financial support provided by the National Science Centre, grant No. 2019/33/B/HS4/01923 entitled “Predictive content of equilibrium exchange rate models”.",

year = "2022",

month = jul,

day = "1",

doi = "10.1016/j.ijforecast.2021.11.001",

language = "English",

volume = "38",

pages = "705--871",

journal = "International Journal of Forecasting",

issn = "0169-2070",

publisher = "Elsevier B.V.",

number = "3",

}

Petropoulos, F, Apiletti, D, Assimakopoulos, V, Babai, MZ, Barrow, DK, Taieb, SB, Bergmeir, C, Bessa, RJ, Bijak, J, Boylan, JE, Browell, J, Carnevale, C, Castle, JL, Cirillo, P, Clements, MP, Cordeiro, C, Oliveira, FLC, Baets, SD, Dokumentov, A, Ellison, J, Fiszeder, P, Franses, PH, Frazier, DT, Gilliland, M, Gonul, MS, Goodwin, P, Grossi, L, Grushka-Cockayne, Y, Guidolin, M, Guidolin, M, Gunter, U, Guo, X, Guseo, R, Harvey, N, Hendry, DF, Hollyman, R, Januschowski, T, Jeon, J, Jose, VRR, Kang, Y, Koehler, AB, Kolassa, S, Kourentzes, N, Leva, S, Li, F, Litsiou, K, Makridakis, S, Martin, GM, Martinez, AB, Meeran, S, Modis, T, Nikolopoulos, K, Onkal, D, Paccagnini, A, Panagiotelis, A, Panapakidis, I, Pavía, JM, Pedio, M, Pedregal, DJ, Pinson, P, Ramos, P, Rapach, DE, Reade, JJ, Rostami-Tabar, B, Rubaszek, M, Sermpinis, G, Shang, HL, Spiliotis, E, Syntetos, AA, Talagala, PD, Talagala, TS, Tashman, L, Thomakos, D, Thorarinsdottir, T, Todini, E, Arenas, JRT, Wang, X, Winkler, RL, Yusupova, A & Ziel, F 2022, 'Forecasting: theory and practice', International Journal of Forecasting, vol. 38, no. 3, pp. 705-871. https://doi.org/10.1016/j.ijforecast.2021.11.001

TY - JOUR

T1 - Forecasting

T2 - theory and practice

AU - Petropoulos, Fotios

AU - Apiletti, Daniele

AU - Assimakopoulos, Vassilios

AU - Babai, Mohamed Zied

AU - Barrow, Devon K.

AU - Taieb, Souhaib Ben

AU - Bergmeir, Christoph

AU - Bessa, Ricardo J.

AU - Bijak, Jakub

AU - Boylan, John E.

AU - Browell, Jethro

AU - Carnevale, Claudio

AU - Castle, Jennifer L.

AU - Cirillo, Pasquale

AU - Clements, Michael P.

AU - Cordeiro, Clara

AU - Oliveira, Fernando Luiz Cyrino

AU - Baets, Shari De

AU - Dokumentov, Alexander

AU - Ellison, Joanne

AU - Fiszeder, Piotr

AU - Franses, Philip Hans

AU - Frazier, David T.

AU - Gilliland, Michael

AU - Gonul, M. Sinan

AU - Goodwin, Paul

AU - Grossi, Luigi

AU - Grushka-Cockayne, Yael

AU - Guidolin, Mariangela

AU - Guidolin, Massimo

AU - Gunter, Ulrich

AU - Guo, Xiaojia

AU - Guseo, Renato

AU - Harvey, Nigel

AU - Hendry, David F.

AU - Hollyman, Ross

AU - Januschowski, Tim

AU - Jeon, Jooyoung

AU - Jose, Victor Richmond R.

AU - Kang, Yanfei

AU - Koehler, Anne B.

AU - Kolassa, Stephan

AU - Kourentzes, Nikolaos

AU - Leva, Sonia

AU - Li, Feng

AU - Litsiou, Konstantia

AU - Makridakis, Spyros

AU - Martin, Gael M.

AU - Martinez, Andrew B.

AU - Meeran, Sheik

AU - Modis, Theodore

AU - Nikolopoulos, Konstantinos

AU - Onkal, Dilek

AU - Paccagnini, Alessia

AU - Panagiotelis, Anastasios

AU - Panapakidis, Ioannis

AU - Pavía, Jose M.

AU - Pedio, Manuela

AU - Pedregal, Diego J.

AU - Pinson, Pierre

AU - Ramos, Patrícia

AU - Rapach, David E.

AU - Reade, J. James

AU - Rostami-Tabar, Bahman

AU - Rubaszek, Michał

AU - Sermpinis, Georgios

AU - Shang, Han Lin

AU - Spiliotis, Evangelos

AU - Syntetos, Aris A.

AU - Talagala, Priyanga Dilini

AU - Talagala, Thiyanga S.

AU - Tashman, Len

AU - Thomakos, Dimitrios

AU - Thorarinsdottir, Thordis

AU - Todini, Ezio

AU - Arenas, Juan Ramón Trapero

AU - Wang, Xiaoqian

AU - Winkler, Robert L.

AU - Yusupova, Alisa

AU - Ziel, Florian

N1 - Funding information: Jakub Bijak’s work received funding from the European Union’s Horizon 2020 research and innovation programme, grant 870299 QuantMig: Quantifying Migration Scenarios for Better Policy. Clara Cordeiro is partially financed by national funds through FCT – Fundac¸ ˜ao para a Ciˆencia e a Tecnologia under the project UIDB/00006/2020. Fernando Luiz Cyrino Oliveira acknowledges the support of the Coordination for the Improvement of Higher Level Personnel (CAPES) – grant number 001, the Brazilian National Council for Scientific and Technological Development (CNPq) – grant number 307403/2019 0, and the Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ) – grant numbers 202.673/2018 and 211.086/2019. Shari De Baets was funded by the FWO Research Foundation Flanders. Joanne Ellison acknowledges the support of the ESRC FertilityTrends project (grant number ES/S009477/1) and the ESRC Centre for Population Change (grant number ES/R009139/1). Piotr Fiszeder was supported by the National Science Centre project number 2016/21/B/HS4/00662 entitled “Multivariate volatility models - the application of low and high prices”. David T. Frazier has been supported by Australian Research Council (ARC) Discovery Grants DP170100729 and DP200101414, and ARC Early Career Researcher Award DE200101070. Mariangela Guidolin acknowledges the support of the University of Padua, Italy, through the grant BIRD188753/18. David F. Hendry gratefully acknowledges funding from the Robertson Foundation and Nuffield College. Yanfei Kang acknowledges the support of the National Natural Science Foundation of China (number 11701022) and the National Key Research and Development Program (number 2019YFB1404600). Stephan Kolassa would like to thank Tilmann Gneiting for some very helpful tips. Gael M. Martin has been supported by Australian Research Council (ARC) Discovery Grants DP170100729 and DP200101414. Alessia Paccagnini acknowledges the research support by COST Action “Fintech and Artificial Intelligence in Finance - Towards a transparent financial industry” (FinAI) CA19130. Jose M. Pav´ıa acknowledges the support of the Spanish Ministry of Science, Innovation and Universities and the Spanish Agency of Research, co-funded with FEDER funds, grant ECO2017-87245-R, and of Conseller´ıa d’Innovaci´ o, Universitats, Ci`encia i Societat Digital, Generalitat Valenciana – grant number AICO/2019/053. Diego J. Pedregal and Juan Ramon Trapero Arenas acknowledge the support of the European Regional Development Fund and Junta de Comunidades de Castilla-La Mancha (JCCM/FEDER, UE) under the 177 project SBPLY/19/180501/000151 and by the Vicerrectorado de Investigaci´on y Po ´ıtica Cient´ıfica from UCLM through the research group fund program PREDILAB; DOCM 26/02/2020 [2020-GRIN-28770]. David E. Rapach thanks Ilias Filippou and Guofu Zhou for valuable comments. J. James Reade and Han Lin Shang acknowledge Shixuan Wang for his constructive comments. Michał Rubaszek is thankful for the financial support provided by the National Science Centre, grant No. 2019/33/B/HS4/01923 entitled “Predictive content of equilibrium exchange rate models”.

PY - 2022/7/1

Y1 - 2022/7/1

N2 - Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.

AB - Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.

KW - review

KW - encyclopedia

KW - methods

KW - applications

KW - principles

KW - time series

KW - prediction

UR - https://www.scopus.com/pages/publications/85123082516

U2 - 10.1016/j.ijforecast.2021.11.001

DO - 10.1016/j.ijforecast.2021.11.001

M3 - Review article

SN - 0169-2070

VL - 38

SP - 705

EP - 871

JO - International Journal of Forecasting

JF - International Journal of Forecasting

IS - 3

ER -

Forecasting: theory and practice

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