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Predicting chaotic coal prices using a multi-layer perceptron network model

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  • Fan, Xinghua
  • Wang, Li
  • Li, Shasha

Abstract

Coal prices in China has risen steadily and been unusually volatile because of the state's contradictory policies in coal sector. This paper sets up a multi-layer perceptron network model to make short terms prediction after identifying the chaotic characteristics of coal price. Coal prices of Qinhuangdao port are selected as the experiment data. Firstly, coal price time series was studied from the chaotic point of view. Three classic indicators: the maximum Lyapunov exponent, the correlation dimension and the Kolmogorov entropy are adopted to verify the chaotic characteristic. Then a multi-layer perceptron model is proposed to predict the trend of the chaotic coal price. Topology of the MLP 3−11−3 is described in detail. Four measurements in level and directional prediction, namely, mean absolute percentage error, root mean square error, direction statistic and THEIL index, are used to evaluate the performance of the model. The selected model better recognizes the pattern and nonlinear characteristic of the coal price time series compared to the autoregressive integrated moving average model and MLP m−nh−1 model.

Suggested Citation

  • Fan, Xinghua & Wang, Li & Li, Shasha, 2016. "Predicting chaotic coal prices using a multi-layer perceptron network model," Resources Policy, Elsevier, vol. 50(C), pages 86-92.
    • Handle: RePEc:eee:jrpoli:v:50:y:2016:i:c:p:86-92
    DOI: 10.1016/j.resourpol.2016.08.009
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    References listed on IDEAS

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    1. Wang, Qiang & Li, Rongrong, 2016. "Journey to burning half of global coal: Trajectory and drivers of China׳s coal use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 341-346.
    2. Joëts, Marc & Mignon, Valérie, 2012. "On the link between forward energy prices: A nonlinear panel cointegration approach," Energy Economics, Elsevier, vol. 34(4), pages 1170-1175.
    3. Ma, Hengyun & Oxley, Les, 2011. "Are China's energy markets cointegrated?," China Economic Review, Elsevier, vol. 22(3), pages 398-407, September.
    4. Li, Hong-Zhou & Tian, Xian-Liang & Zou, Tao, 2015. "Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function," Applied Energy, Elsevier, vol. 151(C), pages 296-305.
    5. Zhu, Bangzhu & Wei, Yiming, 2013. "Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology," Omega, Elsevier, vol. 41(3), pages 517-524.
    6. Hao, Yu & Zhang, Zong-Yong & Liao, Hua & Wei, Yi-Ming, 2015. "China’s farewell to coal: A forecast of coal consumption through 2020," Energy Policy, Elsevier, vol. 86(C), pages 444-455.
    7. Chen, Zhan-Ming, 2014. "Inflationary effect of coal price change on the Chinese economy," Applied Energy, Elsevier, vol. 114(C), pages 301-309.
    8. Yang, Chi-Jen & Xuan, Xiaowei & Jackson, Robert B., 2012. "China's coal price disturbances: Observations, explanations, and implications for global energy economies," Energy Policy, Elsevier, vol. 51(C), pages 720-727.
    9. Burke, Paul J. & Liao, Hua, 2015. "Is the price elasticity of demand for coal in China increasing?," China Economic Review, Elsevier, vol. 36(C), pages 309-322.
    10. Liu, Ming-Hua & Margaritis, Dimitris & Zhang, Yang, 2013. "Market-driven coal prices and state-administered electricity prices in China," Energy Economics, Elsevier, vol. 40(C), pages 167-175.
    11. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2016. "Day-ahead electricity price forecasting via the application of artificial neural network based models," Applied Energy, Elsevier, vol. 172(C), pages 132-151.
    12. Jiao, Jian-Ling & Ge, Hong-Zhen & Wei, Yi-Ming, 2010. "Impact analysis of China's coal-electricity price linkage mechanism: Results from a game model," Journal of Policy Modeling, Elsevier, vol. 32(4), pages 574-588, July.
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