lynx   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/gam/jijfss/v11y2023i2p77-d1168410.html
   My bibliography  Save this article

Impacts of U.S. Stock Market Crash on South African Top Sector Indices, Volatility, and Market Linkages: Evidence of Copula-Based BEKK-GARCH Models

Author

Listed:
  • Benjamin Mudiangombe Mudiangombe

    (School of Economics, University of Johannesburg, P.O. Box 524, Auckland Park 2006, South Africa)

  • John Weirstrass Muteba Mwamba

    (School of Economics, University of Johannesburg, P.O. Box 524, Auckland Park 2006, South Africa)

Abstract
This paper examines the effects of the Standard and Poor’s 500 (SP500) stock index crash during the global financial crisis and the COVID-19 pandemic periods on the South African top sector indices (basic materials, consumer goods, consumer services, financials, healthcare, industrials, technology, and telecommunication). The results of a copula-based BEKK-GARCH approach technique demonstrate the existence of price and volatility spillover during times of stock crashes. We discover that during a stock crisis, strong shocks and higher volatility spillover effects from the United States (U.S.) SP500 index to the top sector indices of the South African Johannesburg Stock Exchange (JSE) markets are more significant. However, there is no integrated economy, as the results did not show any spillover effects from South Africa to U.S. markets. Furthermore, the Gumbel copulas have higher dependence parameters, implying that extreme co-movements occur in the upper tails, suggesting the possibility of a large transmission of shocks from the SP500 to the eight top sector indices of the JSE and showing an asymmetric dependence between these markets. This result is important for investors willing to invest in the South African sector of equity markets to develop hedging strategies to prevent risk spillover from developed markets.

Suggested Citation

  • Benjamin Mudiangombe Mudiangombe & John Weirstrass Muteba Mwamba, 2023. "Impacts of U.S. Stock Market Crash on South African Top Sector Indices, Volatility, and Market Linkages: Evidence of Copula-Based BEKK-GARCH Models," IJFS, MDPI, vol. 11(2), pages 1-19, June.
    • Handle: RePEc:gam:jijfss:v:11:y:2023:i:2:p:77-:d:1168410
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7072/11/2/77/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7072/11/2/77/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    2. Pretorius, Elna, 2002. "Economic determinants of emerging stock market interdependence," Emerging Markets Review, Elsevier, vol. 3(1), pages 84-105, March.
    3. Shahzad, Syed Jawad Hussain & Kumar, Ronald Ravinesh & Ali, Sajid & Ameer, Saba, 2016. "Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 8-33.
    4. Shamsuddin, Abul F. M. & Kim, Jae H., 2003. "Integration and interdependence of stock and foreign exchange markets: an Australian perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(3), pages 237-254, July.
    5. Dai, Xingyu & Li, Matthew C. & Xiao, Ling & Wang, Qunwei, 2022. "COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis," Resources Policy, Elsevier, vol. 79(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Song, Yuegang & Huang, Ruixian & Paramati, Sudharshan Reddy & Zakari, Abdulrasheed, 2021. "Does economic integration lead to financial market integration in the Asian region?," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 366-377.
    2. Sudharshan Reddy Paramati & Eduardo Roca & Rakesh Gupta, 2016. "Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia," Applied Economics, Taylor & Francis Journals, vol. 48(44), pages 4210-4226, September.
    3. Jie Huang & Haiming Zhou & Nader Ebrahimi, 2022. "Bayesian Bivariate Cure Rate Models Using Copula Functions," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(3), pages 1-9, May.
    4. Bedoui, Rihab & Braiek, Sana & Guesmi, Khaled & Chevallier, Julien, 2019. "On the conditional dependence structure between oil, gold and USD exchange rates: Nested copula based GJR-GARCH model," Energy Economics, Elsevier, vol. 80(C), pages 876-889.
    5. Mohamed, Hazik & Masih, Mansur, 2017. "Stock market comovement among the ASEAN-5 : a causality analysis," MPRA Paper 98781, University Library of Munich, Germany.
    6. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Kumar, Ronald Ravinesh & Mensi, Walid, 2017. "Interdependence and contagion among industry-level US credit markets: An application of wavelet and VMD based copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 310-324.
    7. Okhrin, Ostap & Ristig, Alexander, 2014. "Hierarchical Archimedean Copulae: The HAC Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i04).
    8. Wu, Shaomin, 2014. "Construction of asymmetric copulas and its application in two-dimensional reliability modelling," European Journal of Operational Research, Elsevier, vol. 238(2), pages 476-485.
    9. Katarzyna Baran-Gurgul, 2022. "The Risk of Extreme Streamflow Drought in the Polish Carpathians—A Two-Dimensional Approach," IJERPH, MDPI, vol. 19(21), pages 1-27, October.
    10. Luca Riccetti, 2013. "A copula–GARCH model for macro asset allocation of a portfolio with commodities," Empirical Economics, Springer, vol. 44(3), pages 1315-1336, June.
    11. Daniel Puig & Oswaldo Morales-Nápoles & Fatemeh Bakhtiari & Gissela Landa, 2017. "The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico," SciencePo Working papers Main hal-03389325, HAL.
    12. Wanling Huang & Artem Prokhorov, 2014. "A Goodness-of-fit Test for Copulas," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 751-771, October.
    13. Kleinow, Jacob & Moreira, Fernando, 2016. "Systemic risk among European banks: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 27-42.
    14. Xun Lu & Kin Lai & Liang Liang, 2014. "Portfolio value-at-risk estimation in energy futures markets with time-varying copula-GARCH model," Annals of Operations Research, Springer, vol. 219(1), pages 333-357, August.
    15. Emmanoulides, Christos & Fousekis, Panos, 2014. "Vertical Price Transmission in the US Pork Industry: Evidence from Copula Models," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 15(01), pages 1-12.
    16. Peter Grundke & Kamil Pliszka, 2018. "A macroeconomic reverse stress test," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1093-1130, May.
    17. Kelly, Robert & McCarthy, Yvonne & McQuinn, Kieran, 2012. "Impairment and negative equity in the Irish mortgage market," Journal of Housing Economics, Elsevier, vol. 21(3), pages 256-268.
    18. Ekaterina Dorodnykh, 2014. "Determinants of stock exchange integration: evidence in worldwide perspective," Journal of Economic Studies, Emerald Group Publishing, vol. 41(2), pages 292 - 316, March.
    19. Hematizadeh, Roksana & Tajaddini, Reza, 2024. "A state-dependent international CAPM for partially integrated markets: Using local and US risk factors," Global Finance Journal, Elsevier, vol. 62(C).
    20. Hobæk Haff, Ingrid, 2012. "Comparison of estimators for pair-copula constructions," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 91-105.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijfss:v:11:y:2023:i:2:p:77-:d:1168410. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.
    Лучший частный хостинг