摘要：This paper presents an analysis of the use of artificial neural networks as a strategy for forecasting prices in the context of agribusiness. For this purpose, data were adopted from EMATER/RS (1992-2006) on four specific commodities: soybean, live cattle, corn, and wheat. The methodology adopted during the research followed the steps shown in Hair et al. (2005), using neural network perception. The data discussed demonstrate the possibility of using neural networks as a strategy for predicting the price of agricultural commodities in future markets. However, one should pay attention to the common cognitive bias in the process of decision making, as it is believed that a significant contribution to academia lies there, as well as a starting point for improving management decisions in rural business.
