Price Forecasting of Ribbed Smoked Rubber Sheet No. 3 with a Markov Chain Model
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Published:
Jan 29, 2019
Keywords:
Forecasting Ribbed Rubber Sheet Grade 3 RSS3 Markov Chains Models
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Abstract
This research proposes a Markov Chain model for forecasting the price of ribbed rubber sheet grade 3 (RSS3) in Thailand. The model was parameterized with daily prices from January 2014 to March 2016, with the sample size of 536 sets. This study also considers the effect of sample sizes (536 and 196) and the effect of the number of price interval was at 5, 10, 15, 20, 25, and 30. The transition matrix was parameterized for each case, and the daily prices were simulated for 1,000 values. The case of 536 samples and 15 intervals and the case of 196 samples at 5 intervals have the mean of absolute percentage error close to 4%.
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Engineering Research Articles
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References
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[10] J. Sinthichok, “The unsmoke sheet rubber price forecasting model through support vector machine,”M.S. thesis, Department of Information Technology Management, Faculty of Engineer, Prince of Songkla University, 2012.
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[12] V.G. Kulkarni, Introduction to Modeling and Analysis of Stochastic Systems, 1se ed. Springer-Verlag New York, 2011.
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[15] J. Eckstein, (2002, Dec), YASAI: Yet Another Add-in for Teaching Elementary Monte Carlo Simulation in Excel [Online]. Available: http://pubsonline.informs.org/doi/abs/10.1287/ited.2.2.12.
[16] J. Chuinakhorn and M. Rattanasiriwoo, “The system of rubber price forecast using neural technique. A case study: Rubber Research Institute of Thailand,” M.S. thesis, Department of Information Technology, Faculty of Information Technology, King Mongkut's University of Technology North Bangkok, 2008 (in Thai).
[17] I. Aizenberg, L. Sheremetov, L. Villa-Vargas, and J. Martinez-Muñoz, “Multilayer neural network with multi-valued neurons in time series forecasting of oil production,” Neurocomputing, vol. 175, Part B, pp. 980–989, 2016.
[18] A. Carpinone, M. Giorgio, R. Langella, and A. Testa, “Markov chain modeling for very-shortterm wind power forecasting,” Electric Power Systems Research, vol. 122, pp. 152–158, 2015.
[19] K. C. CHAN, “Market share modelling and forecasting using markov chain and alternative models,” International Journal of Innovative Computing, vol. 11, no. 4, pp. 1205–1218, 2015.
[20] S. Romprasert, “Forecasting of natural rubber ribbed smoked sheets no.3 (RSS3) price in the agricultural futures exchange of Thailand,” Ph.D. dissertation, Department of School of Development Economics, National Institute of Development Administration, 2010.
[2] Rubber Technology Research Centre “Research and development of rubber and Para-wood products under the cooperative network of manufacturers and research units,” Rubber Technology Research Centre, Faculty of Science, Mahidol University, Bangkok, Thailand, 2013.
[3] The Office of Industrial Economic, “Introduction to industrial rubber and rubber products,” Office of Industrial Economics, Bangkok, Thailand, 2014.
[4] Y. Kanasawat, “Thailand board of investment,” Investment Promotion Journal, vol. 23, no. 2, pp. 22–28, 2010.
[5] P. Putzon, “The forecasting of export quantity of the rubber ribbed smoked sheet 1 by Box-Jenkins method,” B. Sc., Department of Mathematics, Faculty of Science, Burapa University, 2013.
[6] P. Tapparak and P. Payakkapong, “Forecasting of agricultural product price in the futures market: A case study of rubber,” in Proceedings of 42nd Kasetsart University Annual Conference, 2003, pp. 125–131.
[7] S. Romprasert “Market efficiency test on RSS3 in agricultural futures exchange,” Applied Economics Journal, vol. 15, no. 2, pp. 55–78, 2008.
[8] S. Thongnok, “Forecasting short run price of smoked rubber no.3 in agricultural futures exchange of Thailand,” M.S. thesis, Department of Graduate School, Chiang Mai University, 2010.
[9] C. Sukpan, C. Chopaiad, and S. Chooduang, “Price forecasting of ribbed smoked rubber sheet no.3 in the agricultural futures market by leading indicators and artificial neural networks,” Thaksin University Journal, vol. 18, no.1, pp. 32–40, 2015.
[10] J. Sinthichok, “The unsmoke sheet rubber price forecasting model through support vector machine,”M.S. thesis, Department of Information Technology Management, Faculty of Engineer, Prince of Songkla University, 2012.
[11] C. Rattanavonsee, “Forecasting the price of rubber in the agricultural futures exchange of thailand,” Veridin E-Journal, Silpakorn University, vol. 6, no. 1, pp. 840–846, 2013.
[12] V.G. Kulkarni, Introduction to Modeling and Analysis of Stochastic Systems, 1se ed. Springer-Verlag New York, 2011.
[13] R. Durrett, Essentials of Stochastic Process. Springer, Cham, 2011.
[14] Y. Zhang, “Prediction of financial time series with hidden markov models” M.S. thesis, Department of School of Computing Science, Simon Fraser University, Canada, 2004.
[15] J. Eckstein, (2002, Dec), YASAI: Yet Another Add-in for Teaching Elementary Monte Carlo Simulation in Excel [Online]. Available: http://pubsonline.informs.org/doi/abs/10.1287/ited.2.2.12.
[16] J. Chuinakhorn and M. Rattanasiriwoo, “The system of rubber price forecast using neural technique. A case study: Rubber Research Institute of Thailand,” M.S. thesis, Department of Information Technology, Faculty of Information Technology, King Mongkut's University of Technology North Bangkok, 2008 (in Thai).
[17] I. Aizenberg, L. Sheremetov, L. Villa-Vargas, and J. Martinez-Muñoz, “Multilayer neural network with multi-valued neurons in time series forecasting of oil production,” Neurocomputing, vol. 175, Part B, pp. 980–989, 2016.
[18] A. Carpinone, M. Giorgio, R. Langella, and A. Testa, “Markov chain modeling for very-shortterm wind power forecasting,” Electric Power Systems Research, vol. 122, pp. 152–158, 2015.
[19] K. C. CHAN, “Market share modelling and forecasting using markov chain and alternative models,” International Journal of Innovative Computing, vol. 11, no. 4, pp. 1205–1218, 2015.
[20] S. Romprasert, “Forecasting of natural rubber ribbed smoked sheets no.3 (RSS3) price in the agricultural futures exchange of Thailand,” Ph.D. dissertation, Department of School of Development Economics, National Institute of Development Administration, 2010.
