Modeling Coffee Price using Jump Diffusion Model: The case of Ethiopia

Abstract

Ethiopian coffee price has significant effect on the economy of the country and its price is highly fluctuated. In this study, we aim at modeling and forecasting the washed Sidama class A grade 3 (WSDA3) coffee price in Ethiopia to reduce the risks associated with this price fluctuation. We used daily closed price data of Ethiopian WSDA3 coffee recorded in the period 31 May 2011 to 30 March 2018 obtained from Ethiopia commodity exchange (ECX) market to analyse the prices fluctuation. The nature of log-returns of the price is asymmetric (negatively skewed) and exhibits high kurtosis. We used a Jump diffusion model to model and forecast the empirical data. The method of maximum likelihood is used to estimate the parameters. We used the root mean square error (RMSE) to test the goodness of fitting for the model to the data. This test indicates that the model performs well.