Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/88877
Title: Forecasting Wheat Prices Based on Past Behavior: Comparison of Different Modelling Approaches
Authors: Dias, Joana 
Rocha, Humberto 
Keywords: Agriculture; Machine learning; Price forecasting; Wheat
Issue Date: 2019
Publisher: Springer
Serial title, monograph or event: LNCS
Volume: 11621
Abstract: Being able to accurately forecast the evolution of wheat prices can be a valuable tool. Most of the published works apply classical forecasting models to wheat price time series, and they do not always perform out-of-sample testing. This work compares five modelling approaches for wheat price forecasts, using only past values of the time series. The models performance is assessed considering out-of-sample data only, by considering a sliding and growing time window that will define the data used to determine the models parameters, and the data used for out-of-sample forecasts.
URI: http://hdl.handle.net/10316/88877
ISBN: 978-3-030-24301-2
DOI: 10.1007/978-3-030-24302-9_13
Rights: openAccess
Appears in Collections:I&D CeBER - Livros e Capítulos de Livros

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