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Testing for short explosive bubbles: A case of Brent oil futures price

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  • Wang, Shaoping
  • Feng, Hao
  • Gao, Da

Abstract

This paper considers the problem of detecting short explosive bubbles in financial data. Based on the backward sup Dickey-Fuller (BSDF), we propose a modified version of BSDF, namely mBSDF. We define the dating statistics by adding a modified term to the BSDF, enhancing the bubble emergence signal. We demonstrate the asymptotic distribution and the bubble duration estimates. A series of Monte Carlo simulations show that mBSDF significantly outperforms BSDF for shorter bubbles, and mBSDF can improve the bubble detection rate by up to 22.7%. As an empirical application, we apply the methods to the Brent crude oil futures price and the results confirm that mBSDF detects the latest oil spike shocked by the Russia-Ukraine conflict and almost all periods of explosive bubbles the oil market has experienced in recent years in contrast to BSDF, which further supports the superiority of mBSDF.

Suggested Citation

  • Wang, Shaoping & Feng, Hao & Gao, Da, 2023. "Testing for short explosive bubbles: A case of Brent oil futures price," Finance Research Letters, Elsevier, vol. 52(C).
    • Handle: RePEc:eee:finlet:v:52:y:2023:i:c:s1544612322006730
    DOI: 10.1016/j.frl.2022.103497
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    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1043-1078, November.
    2. Wen-Yuan Lin & I-Chun Tsai, 2016. "Asymmetric Fluctuating Behavior of China's Housing Prices," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 24(2), pages 107-126, March.
    3. David I. Harvey & Stephen J. Leybourne & Robert Sollis, 2015. "Recursive Right-Tailed Unit Root Tests for an Explosive Asset Price Bubble," Journal of Financial Econometrics, Oxford University Press, vol. 13(1), pages 166-187.
    4. Bettendorf, Timo & Chen, Wenjuan, 2013. "Are there bubbles in the Sterling-dollar exchange rate? New evidence from sequential ADF tests," Economics Letters, Elsevier, vol. 120(2), pages 350-353.
    5. Peter C. B. Phillips & Jun Yu, 2011. "Dating the timeline of financial bubbles during the subprime crisis," Quantitative Economics, Econometric Society, vol. 2(3), pages 455-491, November.
    6. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    7. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    8. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert & Taylor, A.M. Robert, 2016. "Tests for explosive financial bubbles in the presence of non-stationary volatility," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 548-574.
    9. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Limit Theory Of Real‐Time Detectors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1079-1134, November.
    10. Nicholas Apergis & Arusha Cooray & Mobeen Ur Rehman, 2018. "Do Energy Prices Affect U.S. Investor Sentiment?," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 19(2), pages 125-140, April.
    11. Phillips, Peter C.B. & Shi, Shu-Ping, 2018. "Financial Bubble Implosion And Reverse Regression," Econometric Theory, Cambridge University Press, vol. 34(4), pages 705-753, August.
    12. Nguyen, Quynh Nhu & Waters, George A., 2022. "Detecting periodically collapsing bubbles in the S&P 500," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 83-91.
    13. Yizhi Wang & Florian Horky & Lennart J. Baals & Brian M. Lucey & Samuel A. Vigne, 2022. "Bubbles all the way down? Detecting and date-stamping bubble behaviours in NFT and DeFi markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 20(4), pages 415-436, October.
    14. Almudhaf, Fahad, 2017. "Speculative bubbles and irrational exuberance in African stock markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 28-32.
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    Cited by:

    1. Panpan Zhu & Qingjie Zhou & Yinpeng Zhang, 2024. "Investor attention and consumer price index inflation rate: Evidence from the United States," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    2. Chen, Weijia & Huang, Shupei & An, Haizhong, 2023. "Revealing dynamic intrinsic temporal and spatial scale characteristics of oil price volatility in bubble and non-bubble periods," Finance Research Letters, Elsevier, vol. 55(PA).
    3. Zhang, Qi & Yang, Kun & Hu, Yi & Jiao, Jianbin & Wang, Shouyang, 2023. "Unveiling the impact of geopolitical conflict on oil prices: A case study of the Russia-Ukraine War and its channels," Energy Economics, Elsevier, vol. 126(C).
    4. Assaf, Ata & Demir, Ender & Ersan, Oguz, 2024. "Detecting and date-stamping bubbles in fan tokens," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 98-113.
    5. Nicolas Cofre & Magdalena Mosionek-Schweda, 2023. "A simulated electronic market with speculative behaviour and bubble formation," Papers 2311.12247, arXiv.org.

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