This research deals with the usefulness of times series models as a tool for buy and sell decisions of the Brazilian BM&F future contracts, in dates nearby the expiration. The models considered were ARIMA, Artificial Neural Networks and Dynamic Linear Models. The data corresponds to the weekly quotations of coffee, soybeans and live cattle prices in the spot and futures markets, between 1996 and 1999. The main objective is to calculate the medium returns of each model in buy and sell operations, in way to provide an indication of the potentials or limitations of each one, using the Sharpe Index as a comparison tool. The results indicate the financial returns are positive in most of the analyzed contracts, indicating the potential use of those models in negotiations of contracts for dates close to expiration, with prominence for operations based in the forecasts of the ARIMA and Dynamic Linear Models.
Agricultural Futures Contracts; Decision Making; Time Series
