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Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model

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  • Liang, Chao
  • Xia, Zhenglan
  • Lai, Xiaodong
  • Wang, Lu

Abstract

This study aims to analyzes the predictability of the natural gas volatility by considering extreme weather information. Based on extended GARCH-MIDAS models, empirical results show that the predictive model adding weather indicators can indeed outperform the model without weather indicators. Importantly, some extreme weather indicators can provide more valuable information to predict the natural gas volatility based on the various out-of-sample tests. Our new weather-related GARCH-MIDAS-ES model can exhibit a new insight on the natural gas volatility forecasting.

Suggested Citation

  • Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    • Handle: RePEc:eee:eneeco:v:116:y:2022:i:c:s0140988322005667
    DOI: 10.1016/j.eneco.2022.106437
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    20. Hailemariam, Abebe & Smyth, Russell, 2019. "What drives volatility in natural gas prices?," Energy Economics, Elsevier, vol. 80(C), pages 731-742.

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