CORDIS Project
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This project develops a methodology for analyzing and forecasting agricultural commodity prices using econometric and machine learning techniques. It aims to create an open-source tool that interprets complex market variables to enhance understanding of food trade.
This is a proposal for a comprehensive methodology for medium-term analysis and forecasting (CMAF) of monthly global prices of agricultural commodities.
The project will create a tool based on this methodology, which provides a detailed explanation of the forecasts and enables their complete interpretation.
Integrating eight econometric and machine learning (ML) methods, CMAF will combine the joint effects of over 100 possible variables.
In addition, it will consider the inclusion of additional…
WIRTSCHAFTSUNIVERSITAT WIEN
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