Prediction of Agriculture Commodities Price Returns Using ARMA and Wavelet

Abstract

This Alongside the market participants who calculate the market impact on international events as well as domestic events, price recording has also become crucial for market participants involved in the agricultural policy. Due to large variation in the commodity prices, many around the globe are busy in evaluating the best procedure for its forecasting. This paper demonstrates the techniques that predict the market prices of grains using ARMA and wavelet transformation. A monthly data from July 1983 to July 2013, with 300 observations have been used. After checking the precision of these models with the help of three different error tests, it turns out, that wavelet forecasting method is best for grain market prices.

Keywords: ARMA, Wavelet, Wheat, Rice, Maize, Barley, Error Analysis