Progress accuracy of CPO price prediction: Evidence from ARMA family and artificial neural network approach

International Research Journal of Finance and Economics

Volumn 64, Issue , 2011, Pages 66-79

  Karia, Abdul Aziz ^a   Bujang, Imbarine ^a  

^a UNIVERSITI TEKNOLOGI MARA   (Malaysia)

Author keywords

ANN; Box jenkins (BJ); Crude palm oil; MSE; NAR; RMSE

Indexed keywords

EID: 79955551242     PISSN: 14502887     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. Arshad, F.M., and Mohamed, Z., (1995). Price discovery trough crude palm oil, Third annual congress on capitalizing and global, Universiti Putra Malaysia, 73-92
2. Cadenas, E., and Rivera, W., (2010). Wind speed forecasting in three different regions of Mexico, using hybrid ARIMA-ANN model, Renewable energy, Elsevier 35, 2732-2738.
3. Diebold, F.X., & Mariano, R.S (1995). Comparing predictive accuracy, Journal of business economics statistic. 13 (3), 3-25
4. Duy, V.T., Sato, Y., and Inoguchi, Y., (2009) Improving accuracy of host load prediction on computational grids by artificial neural networks. Pergamon, Elsevier.
5. Hanke, J.E., and Wichern, D.W., (2009). Business forecasting, Pearson International edition Ninth edition, 399-512.
6. Khashei, M., Bijari, M., and Ardali, G.A.R., (2009). Improvement of auto-regressive integrated moving average using fuzzy logic and artificial neural networks, Neurocomputing, Elsevier 72, 956-967.
7. Kim, T.Y., Oh, K.J., K, C., and D, J.D., (2004). Artificial neural networks for non-stationary time series, Neurocomputing, Elsevier 61, 439-447
8. Maia, A.L.S., Carvalho, F.A.T., and Ludermir, T.B., (2008). Forecasting models for intervalvalued time series, Neurocomputing, Elsevier 71, 3344-3352.
9. Maier, H.R., and Dandy, G.C., (1996). Neural network models for forecasting Univariate time series, Water resource research, v 32 i4, 1013-1022
10. Ming, K.K., and Chandramohan, D., (2002). Malaysian palm oil industry at crossroads and its future direction, Malaysian Palm Oil Berhad, MPOB Malaysia.
11. Noormahayu, M.N., Khalid, A.R., and Elsadig, M.A., (2009). Financial assessment of oil palm cultivation on peatland in Selangor, Malaysia, Mires and Peat, 2 (5), 1-18
12. Obado, J., Syaukat, Y., and Siregar, H., (2009). The impact of export tax policy on the Indonesian crude palm oil industry, Journal of ISSAAS, 15 (2), 107-119
13. Ong, C.S., Huang, J.J., and Tzeng, G.H., (2005). Model identification of ARIMA family using genetic algorithms, Applied mathematics and computation, Elsevier 164, 885-912
14. Pleanjai, S., Gheewala, S.H., and Garivait, S., (2007). Environment evaluation of biodiesel production from palm oil in a life cycle perspective, Asian journal of energy environment, 8 (1/2), 15-32
15. Valenzuela, O., Rojas, F., Guillen, A., Herrera, L.J., Pomares, H., Marquez, L., and Pasadas, M., (2008). Soft computing technique and ARMA model for time series prediction, Neurocomputing, Elsevier 71, 519-537.
16. Roberts, J.M., (2010). World bank's palm oil development strategy should focus on economic freedom, The Heritage Foundation leadership for America, Paper No. 2426
17. Sallehuddin, R., Shamsuddin, S.M., Hashim, S.Z., and Abraham, A., (2009) Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model, University Technology Malaysia, 1-25.
18. Sfetsos, A., (2002). A novel approach for the forecasting of mean hourly wind speed time series, Renewable energy, Elsevier, 163-174
19. Torres, J.L., Gracia, A., Blas, A.G., and Francisco, A., (2005). Forecast of hourly average wind speed with ARMA models in Navarre (Spain), Solar energy, Elsevier 79, 65-77
20. Valenzuela, O., Rojas, I., Rojas, F., Ponares, H., Herrera, L.J., Guillen, A., Marquez, L., and Pasadas, M., (2008). Hybridization of intelligent techniques and ARIMA models for time series prediction, Fuzzy sets and systems, Elsevier 159, 821-845.
21. Wilson, J.H., and Keating, B., (2009). Business forecasting, McGraw Hill sixth edition, 343-346.
22. Wu, C.L., Chau, K.W., and Fan, C., (2010). Prediction of rainfall using modular artificial neural networks coupled with data-preprocessing techniques, Journal of Hydrology, Elsevier 389, 146-167.