IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v58y2023ipas154461232300661x.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461232300661X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2023.104289?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
    2. Symeonidis, Lazaros & Daskalakis, George & Markellos, Raphael N., 2010. "Does the weather affect stock market volatility?," Finance Research Letters, Elsevier, vol. 7(4), pages 214-223, December.
    3. Zhou, Bo & Zhang, Cheng, 2023. "When green finance meets banking competition: Evidence from hard-to-abate enterprises of China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    4. Li, Ziyang & Chen, Yanjun & Li, Yanlin, 2023. "Top management abnormal turnover and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 89(C).
    5. Xinghe Liu & Jun Gao & Zeyi Chen & Yuqing Huang, 2023. "Depoliticization and Stock Price Crash Risk: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(7), pages 2313-2327, May.
    6. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    7. Zhou, Bo & Ding, Hao, 2023. "How public attention drives corporate environmental protection: Effects and channels," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Dai, Xingyu & Dai, Peng-Fei & Wang, Qunwei & Ouyang, Zhi-Yi, 2023. "The impact of energy-exporting countries’ EPUs on China’s energy futures investors: Risk preference, investment position and investment horizon," Research in International Business and Finance, Elsevier, vol. 64(C).
    9. Shoudong Chen & Yueshan Li, 2023. "Targeted Poverty Alleviation And Stock Price Crash Risk: Evidence From China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 68(04), pages 1271-1301, June.
    10. Zhao, Yi & Dai, Xingyu & Zhang, Dongna & Wang, Qunwei & Cao, Yaru, 2023. "Do weather conditions drive China's carbon-coal-electricity markets systemic risk? A multi-timescale analysis," Finance Research Letters, Elsevier, vol. 51(C).
    11. Xie, Linlin & Liu, Guangqiang & Liu, Boyang, 2023. "Patent pledge policy and stock price crash risk: Evidence from China," Research in International Business and Finance, Elsevier, vol. 65(C).
    12. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    13. Sun, Yuying & Zhang, Xun & Hong, Yongmiao & Wang, Shouyang, 2019. "Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling," Energy Economics, Elsevier, vol. 78(C), pages 165-173.
    14. Gao, Haoyu & Wen, Huiyu & Yu, Shujiaming, 2022. "Weathering information disruption: Typhoon strikes and analysts’ forecast dispersion," Finance Research Letters, Elsevier, vol. 49(C).
    15. Xingyu Dai & Dongna Zhang & Chi Keung Marco Lau & Qunwei Wang, 2023. "Multiobjective portfolio optimization: Forecasting and evaluation under investment horizon heterogeneity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2167-2196, December.
    16. Zhang, Dongna & Dai, Xingyu & Wang, Qunwei & Lau, Chi Keung Marco, 2023. "Impacts of weather conditions on the US commodity markets systemic interdependence across multi-timescales," Energy Economics, Elsevier, vol. 123(C).
    17. Quanying Lu & Yuying Sun & Yongmiao Hong & Shouyang Wang, 2022. "Forecasting interval-valued crude oil prices using asymmetric interval models," Quantitative Finance, Taylor & Francis Journals, vol. 22(11), pages 2047-2061, November.
    18. Kong, Xiaowei & Jin, Yifan & Liu, Lihua & Xu, Jialu, 2023. "Firms' exposures on COVID-19 and stock price crash risk: Evidence from China," Finance Research Letters, Elsevier, vol. 52(C).
    19. Ji, Qiang & Zhang, Dayong, 2019. "China’s crude oil futures: Introduction and some stylized facts," Finance Research Letters, Elsevier, vol. 28(C), pages 376-380.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Das, Kuntal K. & Yaghoubi, Mona, 2024. "Migration fear and stock price crash risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    2. Qiang Ji & Dayong Zhang & Yuqian Zhao, 2022. "Intra-day co-movements of crude oil futures: China and the international benchmarks," Annals of Operations Research, Springer, vol. 313(1), pages 77-103, June.
    3. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
    4. Joseph P. Byrne & Prince Asare Vitenu-Sackey, 2024. "The Macroeconomic Impact of Global and Country-Specific Climate Risk," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(3), pages 655-682, March.
    5. Naeem, Muhammad Abubakr & Gul, Raazia & Shafiullah, Muhammad & Karim, Sitara & Lucey, Brian M., 2024. "Tail risk spillovers between Shanghai oil and other markets," Energy Economics, Elsevier, vol. 130(C).
    6. Lyu, Zhichong & Ma, Feng & Zhang, Jixiang, 2023. "Oil futures volatility prediction: Bagging or combination?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 457-467.
    7. Zhu, Yichen & Ghoshray, Atanu, 2021. "Climate Anomalies and Its Impact on U.S. Corn and Soybean Prices," 2021 Conference, August 17-31, 2021, Virtual 315271, International Association of Agricultural Economists.
    8. Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
    9. Zhou, Bo & Wang, Qunwei, 2024. "FinTech matters in sustainable finance: Does it redistribute the supply of financial services?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    10. Zhang, Dongna & Dai, Xingyu & Wang, Qunwei & Lau, Chi Keung Marco, 2023. "Impacts of weather conditions on the US commodity markets systemic interdependence across multi-timescales," Energy Economics, Elsevier, vol. 123(C).
    11. Gao, Yongjun & Mohd Saleh, Norman & Abdullah, Ahmad Monir & Adznan, Syaima, 2024. "Climate-related disclosures under the TCFD framework and business green innovation: Evidence from China A-share companies," Finance Research Letters, Elsevier, vol. 63(C).
    12. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    13. Hu, Genhua & Jiang, Haifeng, 2023. "Time-varying jumps in China crude oil futures market impacted by COVID-19 pandemic," Resources Policy, Elsevier, vol. 82(C).
    14. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
    15. Chen, Zhonglu & Ye, Yong & Li, Xiafei, 2022. "Forecasting China's crude oil futures volatility: New evidence from the MIDAS-RV model and COVID-19 pandemic," Resources Policy, Elsevier, vol. 75(C).
    16. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    17. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    18. McCulloch, Neil & Natalini, Davide & Hossain, Naomi & Justino, Patricia, 2022. "An exploration of the association between fuel subsidies and fuel riots," World Development, Elsevier, vol. 157(C).
    19. Nicholas Apergis & Alexandros Gabrielsen & Lee Smales, 2016. "(Unusual) weather and stock returns—I am not in the mood for mood: further evidence from international markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(1), pages 63-94, February.
    20. Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen, 2024. "A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 366-390, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:58:y:2023:i:pa:s154461232300661x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.