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Pass-through from temperature intervals to China's commodity futures’ interval-valued returns: Evidence from the varying-coefficient ITS model

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  • Wu, Dan
  • Dai, Xingyu
  • Zhao, Ruikun
  • Cao, Yaru
  • Wang, Qunwei

Abstract

This paper proposes a novel varying-coefficient interval-valued time series (VC-ITS) model to reveal the impact of temperature intervals on China's commodity futures’ interval-valued returns. 14 Chinese commodities futures from 2018 to 2023 were analyzed and results show that temperature intervals have a dynamic impact on crude oil futures interval-valued returns and a static impact on steaming coal futures in the selected energy futures. There is a negative pass-through effect of temperature intervals on almost all selected agricultural futures return intervals. Changes in temperature intervals have almost no pass-through effect on changes in metal futures' interval-valued returns, except for nickel futures.

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  • Wu, Dan & Dai, Xingyu & Zhao, Ruikun & Cao, Yaru & Wang, Qunwei, 2023. "Pass-through from temperature intervals to China's commodity futures’ interval-valued returns: Evidence from the varying-coefficient ITS model," Finance Research Letters, Elsevier, vol. 58(PA).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pa:s154461232300661x
    DOI: 10.1016/j.frl.2023.104289
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    Cited by:

    1. Zhang, Dongna & Dai, Xingyu & Xue, Jianhao, 2024. "Incorporating weather information into commodity portfolio optimization," Finance Research Letters, Elsevier, vol. 66(C).
    2. Babel Raïssa Guemdjo Kamdem & Jules Sadefo Kamdem & Carlos Ogouyandjou, 2024. "An abelian way approach to study random extended intervals and their ARMA processes," Post-Print hal-04506343, HAL.
    3. Haowen Bao & Yongmiao Hong & Yuying Sun & Shouyang Wang, 2024. "Sparse Interval-valued Time Series Modeling with Machine Learning," Papers 2411.09452, arXiv.org.

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