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The Granger Causality of Bahrain Stocks, Bitcoin, and Other Commodity Asset Returns: Evidence of Short-Term Return Spillover Before and During the COVID-19 Pandemic

Author

Listed:
  • Mark Pabatang Doblas

    (University of Technology, Bahrain)

  • Maria Cecilia Lagaras

    (University of Technology, Bahrain)

Abstract

This study examines the tendency of short-term return spillover across Bahrain stocks, bitcoin, and other commodity assets factoring in the dynamic effect of the COVID-19 pandemic. The study employed vector autoregression (VAR) model using the daily returns of Bahrain All Shares Index, bitcoin, crude oil, and gold futures from January 2018 to March 2022. The results showed a persistent unidirectional short-term spillover of return from the Bahrain stock market to the futures gold market for both the period before and during the pandemic. Moreover, the results also showed that the significant positive shock in the bitcoin returns as granger-caused by the returns of the Bahrain stock market is only during the period before the pandemic. Finally, a significant negative contemporaneous short-term effect on the crude oil market returns can be statistically explained by the shocks in the Bahrain stock market only during the COVID-19 period.

Suggested Citation

  • Mark Pabatang Doblas & Maria Cecilia Lagaras, 2023. "The Granger Causality of Bahrain Stocks, Bitcoin, and Other Commodity Asset Returns: Evidence of Short-Term Return Spillover Before and During the COVID-19 Pandemic," International Journal of Business Analytics (IJBAN), IGI Global, vol. 10(1), pages 1-20, January.
    • Handle: RePEc:igg:jban00:v:10:y:2023:i:1:p:1-20
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    References listed on IDEAS

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    1. Venus Khim-Sen Liew, 2004. "Which Lag Length Selection Criteria Should We Employ?," Economics Bulletin, AccessEcon, vol. 3(33), pages 1-9.
    2. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    3. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
    4. Kim, Bong-Han & Kim, Hyeongwoo & Lee, Bong-Soo, 2015. "Spillover effects of the U.S. financial crisis on financial markets in emerging Asian countries," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 192-210.
    5. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    6. Hans-Martin Krolzig, 2001. "General--to--Specific Reductions of Vector Autoregressive Processes," Computing in Economics and Finance 2001 164, Society for Computational Economics.
    7. Zeng, Ting & Yang, Mengying & Shen, Yifan, 2020. "Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks," Economic Modelling, Elsevier, vol. 90(C), pages 209-220.
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