Forecasting the Ethiopian Coffee Price Using Kalman Filtering Algorithm

  • 1. Department of mathematics, Bahir Dar University, Bahir Dar, P.O.Box 3018, Ethiopia;
    2. Department of mathematics, Kotebe Metropolitan University, Addis Ababa, P.O.Box 31248, Ethiopia

Received date: 2017-10-09

  Revised date: 2018-01-20

  Online published: 2018-05-30


Ethiopian coffee price is highly fluctuated and has significant effect on the economy of the country. Conducting a research on forecasting coffee price has theoretical and practical importance.This study aims at forecasting the coffee price in Ethiopia. We used daily closed price data of Ethiopian coffee recorded in the period 25 June 2008 to 5 January 2017 obtained from Ethiopia commodity exchange (ECX) market to analyse coffee prices fluctuation. Here, the nature of coffee price is non-stationary and we apply the Kalman filtering algorithm on a single linear state space model to estimate and forecast an optimal value of coffee price. The performance of the algorithm for estimating and forecasting the coffee price is evaluated by using root mean square error (RMSE). Based on the linear state space model and the Kalman filtering algorithm, the root mean square error (RMSE) is 0.000016375, which is small enough, and it indicates that the algorithm performs well.

Cite this article

Tesfahun Berhane, Nurilign Shibabaw, Aemiro Shibabaw, Molalign Adam, Abera A. Muhamed . Forecasting the Ethiopian Coffee Price Using Kalman Filtering Algorithm[J]. Journal of Resources and Ecology, 2018 , 9(3) : 302 -305 . DOI: 10.5814/j.issn.1674-764x.2018.03.010


[1] Costas milas, Jesus Otero and Theodore Panagiotidis.2004. Forecasting the spot prices of various coffee types using linear and non-linear error correction models,international journal of finance and economics, 9: 277-288.
[2] International Coffee Council (ICO). 2014.Fourth ICO World Coffee Conference: Proposal received from Ethiopia. London: International Coffee Council, 1-2.
[3] Labouisse J. P., Bellachew B., Kotecha, al.2008.Current Status of Coffee (Coffee Arabica L.) Genetic Resources in Ethiopia: Implications for Conservation.GenetResour Crop, 55: 1079-1093.
[4] Naveena K., Subedar Singh, SantoshaRathod,et al.2017. Hybrid Time Series Modeling for Forecasting the Price of Washed Coffee (Arabica Plantation Coffee) in India. International Journal of Agriculture Sciences, 9(10): 4004-4007.
[5] Rafiee, J. &Tse, P.W.2009.Use of autocorrelation of wavelet coefficients for fault diagnosis,Mechanical Systems and Signal Processing, 23: 1554-1572.
[6] Overseas development Institute (ODI). 2009. Ethiopia Trademarking and Licensing Initiative: Supporting a Better Deal for Coffee Producers through Aid for Trade, 1-3.
[7] Yan Xu, Guosheng Zhang.2015. Application of Kalman Filter in the Prediction of Stock Price.International Symposium on Knowledge Acquisition and Modeling (KAM). Atlantis press, 197-198.
[8] Worako Schalkwyk V., Alemu, et al.Alemu, ., 2008.Producer price and price transmission in a deregulated Ethiopian coffee market.Agrekon, 47(4): 492-508.
[9] ZHU Meifeng and ZHAO Guohao.2015. Forecasting the Coke Price Based on the Kalman Filtering Algorithm.Journal of Resources and Ecology, 6(1): 60-64.