The influence of behavior factors in setting the agricultural futures market prices

Abstract

The great challenge for this research work is to show that the biases of investor behavior are predictable and may affect the coffee futures market prices. This research work uses auto-regressive conditional heteroskedasticity (ARCH) models to analyze results that cause deviations in the coffee futures market prices. The negative asymmetry coefficient of EGARCH model and the positive asymmetry coefficient of TGARCH model show the presence of the leverage effect where negative shocks have a greater impact in the volatility of returns in coffee than positive shocks. The presence of the leverage effect corroborates the Prospect Theory. Model results also show that the reactions of investors to negative information were statistically significant in the coffee futures market and suggest that Behavioral Finance might contribute to the understanding of the formation of coffee futures market prices.