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Intraday momentum and return predictability: Evidence from the crude oil market

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  • Wen, Zhuzhu
  • Gong, Xu
  • Ma, Diandian
  • Xu, Yahua
Abstract
Intraday return predictability has firstly been identified in the equity markets, and we extend the analysis to the crude oil market by using high-frequency United States Oil Fund data from 2006 to 2018. We find a different intraday prediction pattern in the oil market, where only the first half-hour returns positively predict the last half-hour returns. A market timing strategy based on these findings generates substantial profits. We further decompose the first half-hour return into its overnight and open half-hour components and find that the former contains more predictive information. The economic mechanisms of infrequent portfolio rebalancing and the presence of late-informed investors explain our findings. Notably, unlike equity markets, the oil market exhibits a unique intraday trading volume pattern due to the release of two routine oil inventory announcements. However, the information contained in the inventory announcements does not offer predictability for the last half-hour returns.

Suggested Citation

  • Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    • Handle: RePEc:eee:ecmode:v:95:y:2021:i:c:p:374-384
    DOI: 10.1016/j.econmod.2020.03.004
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    Cited by:

    1. Michał Dominik Stasiak & Żaneta Staszak, 2024. "Modelling and Forecasting Crude Oil Prices Using Trend Analysis in a Binary-Temporal Representation," Energies, MDPI, vol. 17(14), pages 1-13, July.
    2. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    3. Chien-Yuan Lai & Zhen-Yu Lin & Cheoljun Eom & Ping-Chen Tsai, 2022. "Market Intraday Momentum with New Measures for Trading Cost: Evidence from KOSPI Index," JRFM, MDPI, vol. 15(11), pages 1-12, November.
    4. Wang, Cheng & Bouri, Elie & Xu, Yahua & Zhang, Dingsheng, 2023. "Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks," Energy Economics, Elsevier, vol. 127(PB).
    5. Zhang, Wei & Wang, Pengfei & Li, Yi, 2021. "Bond intraday momentum," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    6. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    7. repec:ags:aaea22:335655 is not listed on IDEAS
    8. Sultan Alturki & Alexander Kurov, 2022. "Market inefficiencies surrounding energy announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 172-188, January.
    9. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Zhenjie Wang & Jiewei Zhang & Hafeez Ullah, 2023. "Exploring the Multidimensional Perspective of Retail Investors’ Attention: The Mediating Influence of Corporate Governance and Information Disclosure on Corporate Environmental Performance in China," Sustainability, MDPI, vol. 15(15), pages 1-33, August.
    11. Ming, Lei & Song, Wuqi & Dong, Minyi, 2023. "Revisiting time series momentum in China's commodity futures market: Evidence on sources of momentum profits," Economic Modelling, Elsevier, vol. 128(C).

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    More about this item

    Keywords

    Intraday momentum; Return predictability; Crude oil market; Market timing strategy;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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