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Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks

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  • Wang, Cheng
  • Bouri, Elie
  • Xu, Yahua
  • Zhang, Dingsheng

Abstract

This study examines the possible impacts of various market shocks, covering oil-related regular news releases and extreme shocks on the intraday and overnight variations in tail risk and intraday return predictability in the crude oil market using high-frequency United States Oil Fund (USO) data from April 10, 2008, to May 10, 2022. First, we find that both regular news and extreme shocks significantly impact the distribution of tail risk during daytime trading and overnight non-trading sessions, with the latter showing stronger effects. Second, extreme shocks have a greater impact on intraday return predictability, with most market shocks obliterating the predictive power of first half-hour returns. Third, the predictability of the first half-hour returns comes primarily from the market opening session from 9:30 am to 10:00 am, and overnight returns lose their predictability. These results have important implications for both market participants and policymakers.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:eneeco:v:127:y:2023:i:pb:s0140988323006199
    DOI: 10.1016/j.eneco.2023.107121
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    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Gupta, Rangan & Yoon, Seong-Min, 2018. "OPEC news and predictability of oil futures returns and volatility: Evidence from a nonparametric causality-in-quantiles approach," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 206-214.
    3. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    4. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    5. Wong, Patrick, 2023. "Explaining intraday crude oil returns with higher order risk-neutral moments," Journal of Commodity Markets, Elsevier, vol. 31(C).
    6. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    7. Peter F. Christoffersen & Francis X. Diebold & Til Schuermann, 1998. "Horizon problems and extreme events in financial risk management," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Oct), pages 109-118.
    8. Qian, Lihua & Zeng, Qing & Lu, Xinjie & Ma, Feng, 2022. "Global tail risk and oil return predictability," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    10. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process," Energy Economics, Elsevier, vol. 42(C), pages 343-354.
    11. Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "News-based equity market uncertainty and crude oil volatility," Energy, Elsevier, vol. 222(C).
    12. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    13. Chatziantoniou, Ioannis & Gabauer, David & Perez de Gracia, Fernando, 2022. "Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 111(C).
    14. Muravyev, Dmitriy & Ni, Xuechuan (Charles), 2020. "Why do option returns change sign from day to night?," Journal of Financial Economics, Elsevier, vol. 136(1), pages 219-238.
    15. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    16. Güntner, Jochen H. F., 2014. "How Do International Stock Markets Respond To Oil Demand And Supply Shocks?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(8), pages 1657-1682, December.
    17. Georgios Sermpinis & Jason Laws & Christian L. Dunis, 2013. "Modelling and trading the realised volatility of the FTSE100 futures with higher order neural networks," The European Journal of Finance, Taylor & Francis Journals, vol. 19(3), pages 165-179, March.
    18. Ye, Shiyu & Karali, Berna, 2016. "The informational content of inventory announcements: Intraday evidence from crude oil futures market," Energy Economics, Elsevier, vol. 59(C), pages 349-364.
    19. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight momentum, informational shocks, and late informed trading in China," International Review of Financial Analysis, Elsevier, vol. 66(C).
    20. Diego R. Känzig, 2021. "The Macroeconomic Effects of Oil Supply News: Evidence from OPEC Announcements," American Economic Review, American Economic Association, vol. 111(4), pages 1092-1125, April.
    21. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    22. 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.
    23. Brandt, Michael W. & Gao, Lin, 2019. "Macro fundamentals or geopolitical events? A textual analysis of news events for crude oil," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 64-94.
    24. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    25. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    26. Herrera, Ana María & Karaki, Mohamad B., 2015. "The effects of oil price shocks on job reallocation," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 95-113.
    27. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    28. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    29. Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023. "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 54-77.
    30. Lou, Dong & Polk, Christopher & Skouras, Spyros, 2019. "A tug of war: overnight versus intraday expected returns," LSE Research Online Documents on Economics 87481, London School of Economics and Political Science, LSE Library.
    31. Lou, Dong & Polk, Christopher & Skouras, Spyros, 2019. "A tug of war: Overnight versus intraday expected returns," Journal of Financial Economics, Elsevier, vol. 134(1), pages 192-213.
    32. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
    33. Berkman, Henk & Koch, Paul D. & Tuttle, Laura & Zhang, Ying Jenny, 2012. "Paying Attention: Overnight Returns and the Hidden Cost of Buying at the Open," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(4), pages 715-741, August.
    34. Brian M Weller, 2019. "Measuring Tail Risks at High Frequency," Review of Financial Studies, Society for Financial Studies, vol. 32(9), pages 3571-3616.
    35. Bregantini, Daniele, 2013. "Moment-based estimation of stochastic volatility," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4755-4764.
    36. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    37. Arjun Chatrath & Hong Miao & Sanjay Ramchander, 2012. "Does the price of crude oil respond to macroeconomic news?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(6), pages 536-559, June.
    38. Liu, Qingfu & Tse, Yiuman, 2017. "Overnight returns of stock indexes: Evidence from ETFs and futures," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 440-451.
    39. Xu Gong & Boqiang Lin, 2021. "Effects of structural changes on the prediction of downside volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1124-1153, July.
    40. Hendershott, Terrence & Livdan, Dmitry & Rösch, Dominik, 2020. "Asset pricing: A tale of night and day," Journal of Financial Economics, Elsevier, vol. 138(3), pages 635-662.
    41. Shaikh, Imlak, 2021. "On the relation between Pandemic Disease Outbreak News and Crude oil, Gold, Gold mining, Silver and Energy Markets," Resources Policy, Elsevier, vol. 72(C).
    42. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    43. Ma, Feng & Liao, Yin & Zhang, Yaojie & Cao, Yang, 2019. "Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 40-55.
    44. Bogousslavsky, Vincent, 2021. "The cross-section of intraday and overnight returns," Journal of Financial Economics, Elsevier, vol. 141(1), pages 172-194.
    45. Naqvi, Bushra & Mirza, Nawazish & Rizvi, Syed Kumail Abbas & Porada-Rochoń, Małgorzata & Itani, Rania, 2021. "Is there a green fund premium? Evidence from twenty seven emerging markets," Global Finance Journal, Elsevier, vol. 50(C).
    46. Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2022. "Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 134-157, January.
    47. Karaki, Mohamad B., 2017. "Nonlinearities in the response of real GDP to oil price shocks," Economics Letters, Elsevier, vol. 161(C), pages 146-148.
    48. Adamolekun, Gbenga & Sakariyahu, Rilwan & Lawal, Rodiat & Ahmed, Ammar, 2023. "Electronic trading and stock market participation in Africa: Does technology induce participation?," Economics Letters, Elsevier, vol. 224(C).
    49. Hooker, Mark A., 1996. "What happened to the oil price-macroeconomy relationship?," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 195-213, October.
    50. 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.
    51. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2020. "Sequential forecasting of downside extreme risk during overnight and daytime: Evidence from the Chinese Stock Market☆," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    52. Amaya, Diego & Filbien, Jean-Yves & Okou, Cédric & Roch, Alexandre F., 2018. "Distilling liquidity costs from limit order books," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 16-34.
    53. Herrera, Ana María & Karaki, Mohamad B. & Rangaraju, Sandeep Kumar, 2017. "Where do jobs go when oil prices drop?," Energy Economics, Elsevier, vol. 64(C), pages 469-482.
    54. Riedel, Christoph & Wagner, Niklas, 2015. "Is risk higher during non-trading periods? The risk trade-off for intraday versus overnight market returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 53-64.
    55. Diego Amaya & Jean-Yves Filbien & Cédric Okou & Alexandre Roch, 2018. "Distilling liquidity costs from limit order books," Post-Print hal-04409561, HAL.
    56. Baltussen, Guido & Da, Zhi & Lammers, Sten & Martens, Martin, 2021. "Hedging demand and market intraday momentum," Journal of Financial Economics, Elsevier, vol. 142(1), pages 377-403.
    57. Andersen, Torben G. & Bollerslev, Tim & Cai, Jun, 2000. "Intraday and interday volatility in the Japanese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(2), pages 107-130, June.
    58. Liao, Huei-Chu & Lee, Yi-Huey & Suen, Yu-Bo, 2008. "Electronic trading system and returns volatility in the oil futures market," Energy Economics, Elsevier, vol. 30(5), pages 2636-2644, September.
    59. Liu, Qingfu & An, Yunbi, 2014. "Risk contributions of trading and non-trading hours: Evidence from Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 17-29.
    60. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
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    More about this item

    Keywords

    Overnight and intraday returns; Tail risks; Regular news releases; Extreme shocks; Intraday return predictability;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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