Abstract

We investigated the effect of the 2007 to 2008 Brazilian financial crisis on nonlinearity and the prediction accuracy of artificial neural networks on monthly soybean prices in Brazil. To determine the exogenous variable, the commodity’s logarithm return was calculated. The best period for the series simulation was then identified, simulations carried out and the model validated. Model forecasting results were satisfactory for all samples. A group method of data handling (GMDH) methodology was capable of demonstrating the returns’ non-randomness, denoting marketing inefficiency, arbitrage opportunities and abnormal return to investors, especially after the financial crisis of 2007 to 2008.

Key words: Financial crisis, predictability, nonlinearity, soybean.