Título :	A review of artificial intelligence quality in forecasting asset prices
Autor :	Barboza, Flavio Silva, Geraldo Nunes Fiorucci, José Augusto
metadata.dc.contributor.affiliation:	Federal University of Uberlândia, School of Business and Management São Paulo State University, Institute of Biosciences, Humanities and Exact Sciences, Mathematics Department University of Brasilia, Department of Statistics
Assunto::	Séries temporais Aprendizado de máquina
Fecha de publicación :	2-abr-2023
Editorial :	John Wiley & Sons Ltd.
Citación :	BARBOZA, Flavio, SILVA, Geraldo Nunes, FIORUCCI, José Augusto. A review ofartificial intelligence quality in forecasting assetprices. Journal of Forecasting, v. 42, n. 7, 1708-1728, 2023. DOI: https://doi.org/10.1002/for.2979.
Abstract:	Researchers and practitioners globally, from a range of perspectives, acknowl- edge the difficulty in determining the value of a financial asset. This subject is of utmost importance due to the numerous participants involved and its impact on enhancing market structure, function, and efficiency. This paper conducts a comprehensive review of the academic literature to provide insights into the reasoning behind certain conventions adopted in financial value estimation, including the implementation of preprocessing techniques, the selection of relevant inputs, and the assessment of the performance of computational models in predicting asset prices over time. Our analysis, based on 109 studies sourced from 10 databases, reveals that daily forecasts have achieved average error rates of less than 1.5%, while monthly data only attain this level in optimal circumstances. We also discuss the utilization of tools and the integration of hybrid models. Finally, we highlight compelling gaps in the literature that provide avenues for further research.
metadata.dc.description.unidade:	Instituto de Ciências Exatas (IE) Departamento de Estatística (IE EST)
DOI:	https://doi.org/10.1002/for.2979
metadata.dc.relation.publisherversion:	https://onlinelibrary.wiley.com/doi/10.1002/for.2979
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