Probability density forecasts for steam coal prices in China: The role of high-frequency factors

Coal plays a key role in China's economy as a dominant primary energy resource. In this paper, we provide probability density forecasts for weekly steam coal prices in China based on daily factors such as renewable energy source, Daqing oil, Japanese natural gas, Australia steam coal prices, coal mining industry index, A-share power sector index, A-share index, coal industry index, and temperature. The empirical results show that the influence of temperature lasts longer than other factors, while the Australia steam coal prices, renewable energy source and A-share index are the three best predictors for steam coal prices. It is also shown that the high-frequency factors are useful to forecast steam coal prices and that considering the nonlinearity of coal prices can improve the forecast accuracy by about 22%. We further provide the probability density forecasts for steam coal prices based on the influence of all the selected factors, the results suggest that our proposed method can provide accurate and satisfying probability density forecasts. Given these results, the policy-makers can make effective strategies which can not only adjust the energy structure but also ensure economic growth. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This study provides probability density forecasts for steam coal prices in China based on various factors, showing that temperature has the longest influence, while Australia steam coal prices, renewable energy source, and A-share index are the best predictors. Considering the nonlinearity can significantly improve forecast accuracy.