Please use this identifier to cite or link to this item:
https://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: | https://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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File | Description | Size | Format | |
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ICCSA2019_3.pdf | Forecasting Wheat Prices Based on Past Behavior | 1.53 MB | Adobe PDF | View/Open |
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