Forecasting: theory and practice

Petropoulos, Fotios, Apiletti, Daniele, Assimakopoulos, Vassilios, Babai, Mohamed Zied, Barrow, Devon K., Taieb, Souhaib Ben, Bergmeir, Christoph, Bessa, Ricardo J., Bijak, Jakub, Boylan, John E., Browell, Jethro, Carnevale, Claudio, Castle, Jennifer L., Cirillo, Pasquale, Clements, Michael P., Cordeiro, Clara, Oliveira, Fernando Luiz Cyrino, De Baets, Shari, Dokumentov, Alexander, Ellison, Joanne, Fiszeder, Piotr, Franses, Philip Hans, Frazier, David T., Gilliland, Michael, Gonul, Sinan, Goodwin, Paul, Grossi, Luigi, Grushka-Cockayne, Yael, Guidolin, Mariangela, Guidolin, Massimo, Gunter, Ulrich, Guo, Xiaojia, Guseo, Renato, Harvey, Nigel, Hendry, David F., Hollyman, Ross, Januschowski, Tim, Jeon, Jooyoung, Jose, Victor Richmond R., Kang, Yanfei, Koehler, Anne B., Kolassa, Stephan, Kourentzes, Nikolaos, Leva, Sonia, Li, Feng, Litsiou, Konstantia, Makridakis, Spyros, Martin, Gael M., Martinez, Andrew B., Meeran, Sheik, Modis, Theodore, Nikolopoulos, Konstantinos, Önkal, Dilek, Alessia Paccagnini, Alessia, Panagiotelis, Anastasios, Panapakidis, Ioannis, Pavia, Jose M., Pedio, Manuela, Pedregal, Diego J., Pinson, Pierre, Ramos, Patricia, Rapach, David E., Reade, J. James, Rostami-Tabar, Bahman, Rubaszek, Michał, Sermpinis, Georgios, Shang, Han Lin, Spiliotis, Evangelos, Syntetos, Aris A., Talagala, Priyanga Dilini, Talagala, Thiyanga S., Tashman, Len, Thomakos, Dimitrios, Thorarinsdottir, Thordis, Todini, Ezio, Trapero Arenas, Juan Ramon, Wang, Xiaoqian, Winkler, Robert L., Yusupova, Alisa and Ziel, Florian (2021) Forecasting: theory and practice. International Journal of Forecasting. ISSN 0169-2070 (In Press)

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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.

Item Type: Article
Additional Information: 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. 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”.
Uncontrolled Keywords: review, encyclopedia, methods, applications, principles, time series, prediction
Subjects: N100 Business studies
Department: Faculties > Business and Law > Newcastle Business School
Depositing User: John Coen
Date Deposited: 04 Nov 2021 11:49
Last Modified: 04 Nov 2021 12:30
URI: http://nrl.northumbria.ac.uk/id/eprint/47631

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