Unbiasedness and Market Efficiency Tests of the U.S. Rice Futures Market

Abstract

This study examines short-run and long-run unbiasedness within the U.S. rice futures market. Standard OLS, cointegration, and error-correction models are used to determine unbiasedness. In addition, the forecasting performance of the rice futures market is analyzed and compared to out-of-sample forecasts derived from an additive ARIMA model and the error-correction model. The results of our unbiasedness tests and the forecasting performance of the rice futures market provide supporting evidence that the U.S. long-grain rough rice futures market is efficient. The results have important price risk management and price discovery implications for Arkansas and U.S. rice industry participants.