The extent of virgin olive-oil prices’ distribution revealing the behavior of market speculators

The major problem facing olive oil producers each winter campaign, contrary to what is expected, is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. The aim of this paper is to study the olive oil price formation mechanisms in order to learn about the traders’ behavior in the olive oil market. We econometrically study the price formation by implementing statistical models and we provide an economic explanation for the stylized facts detected in olive oil price series. For prediction purposes, we use the artificial neural network (ANN) approach. Our main findings indicate that the AR(1)-GJR(1,1) model and the Ornstein–Uhlenbeck process with stochastic volatility succeeded to some extent in capturing the series stylized facts. The unstable participants’ behavior creates the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation ANN approach with input information based on discrete wavelet decomposition and recent price past history.