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Inventory announcements, jump dynamics, volatility and trading volume in U.S. energy futures markets

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  • Bjursell, Johan
  • Gentle, James E.
  • Wang, George H.K.

Abstract

This paper applies nonparametric methods to identify jumps in daily futures prices and intraday jumps surrounding inventory announcements of crude oil, heating oil and natural gas contracts traded on the New York Mercantile Exchange. The sample period of our intraday data covers January 1990 to January 2008. We have obtained several interesting empirical results. (1) Large volatility days are often associated with large jump components, and large jump components are often associated with the Energy Information Administration's inventory announcement dates. (2) The volatility jump component is less persistent than the continuous sample path component. (3) Volatility and trading volume are higher on days with a jump at the inventory announcement than on days without a jump at the announcement. Furthermore, the intraday volatility returns to normal faster following inventory announcements with jumps than after announcements without jumps.

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  • Bjursell, Johan & Gentle, James E. & Wang, George H.K., 2015. "Inventory announcements, jump dynamics, volatility and trading volume in U.S. energy futures markets," Energy Economics, Elsevier, vol. 48(C), pages 336-349.
  • Handle: RePEc:eee:eneeco:v:48:y:2015:i:c:p:336-349
    DOI: 10.1016/j.eneco.2014.11.006
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    Cited by:

    1. Farhangdoost, Sara & Etienne, Xiaoli L., 2020. "Time-Varying Storage Announcement Effect in Natural Gas Market," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304476, Agricultural and Applied Economics Association.
    2. Misund, Bård & Oglend, Atle, 2016. "Supply and demand determinants of natural gas price volatility in the U.K.: A vector autoregression approach," Energy, Elsevier, vol. 111(C), pages 178-189.
    3. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    4. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    5. Olivier Rousse & Benoît Sévi, 2017. "Informed Trading in Oil-Futures Market," Working Papers hal-01460186, HAL.
    6. Rousse, Olivier & Sévi, Benoît, 2016. "Informed Trading in Oil-Futures Market," ESP: Energy Scenarios and Policy 249788, Fondazione Eni Enrico Mattei (FEEM).
    7. Rangan Gupta & Chi Keung Marco Lau & Seong-Min Yoon, 2019. "OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(4), pages 1-23, December.
    8. Ahmad, Wasim & Prakash, Ravi & Uddin, Gazi Salah & Chahal, Rishman Jot Kaur & Rahman, Md. Lutfur & Dutta, Anupam, 2020. "On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?," Energy Economics, Elsevier, vol. 91(C).
    9. Ding, Ashley, 2021. "A state-preference volatility index for the natural gas market," Energy Economics, Elsevier, vol. 104(C).
    10. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    11. Yanting Chen & Peter R. Hartley & Yihui Lan, 2023. "Temperature, storage, and natural gas futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 549-575, April.
    12. Tian, Xiao & Duong, Huu Nhan & Kalev, Petko S., 2019. "Information content of the limit order book for crude oil futures price volatility," Energy Economics, Elsevier, vol. 81(C), pages 584-597.
    13. Song-Zan Chiou-Wei & Sheng-Hung Chen & Wei-Hung Chen, 2023. "Asymmetric Effects of Prices and Storage on Rig Counts: Evidence from the US Natural Gas and Crude Oil Markets," Energies, MDPI, vol. 16(15), pages 1-25, August.
    14. Chiou-Wei, Song-Zan & Chen, Sheng-Hung & Zhu, Zhen, 2020. "Natural gas price, market fundamentals and hedging effectiveness," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 321-337.
    15. Tore S. Kleppe & Atle Oglend, 2019. "Can limits‐to‐arbitrage from bounded storage improve commodity term‐structure modeling?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 865-889, July.
    16. Anabelle Couleau & Teresa Serra & Philip Garcia, 2020. "Are Corn Futures Prices Getting “Jumpy”?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 569-588, March.

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    More about this item

    Keywords

    Realized variation; Bipower variation; Intraday jump statistics; Energy futures price; Trading volume behavior and inventory news events;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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