International commodity, financial and foreign exchange markets operate under conditions of uncertainty, incomplete or asymmetric information. Consequently, their development is nonlinear and does not fir fundamental laws, and therefore cannot be sufficiently predictable. In addition, the export of goods depends on different factors that form multidimensional data sets. It requires sophisticated analytical tools such as Data Mining and Machine Learning to conduct analysis and make accurate management decisions.
Data Mining and Machine Learning Application to Grain Export and Exchange Rates Co-Movement Under Incomplete Information