IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v13y2025i3p36-d1753336.html

Integration and Risk Transmission Dynamics Between Bitcoin, Currency Pairs, and Traditional Financial Assets in South Africa

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
    School of Health Policy and Management, York University, Toronto, ON M3J 1P3, Canada
    La Haute École de Commerce de Kinshasa, Avenue de la Révolution, Gombe, Kinshasa B.P. 16596, Democratic Republic of the Congo)

Abstract

This study explores the new insights into the integration and dynamic asymmetric volatility risk spillovers between Bitcoin, currency pairs (USD/ZAR, GBP/ZAR and EUR/ZAR), and traditional financial assets (ALSI, Bond, and Gold) in South Africa using daily data spanning the period from 2010 to 2024 and employing Time-Varying Parameter Vector Autoregression (TVP-VAR) and wavelet coherence. The findings revealed strengthened integration between traditional financial assets and currency pairs, as well as weak integration with BTC/ZAR. Furthermore, BTC/ZAR and traditional financial assets were receivers of shocks, while the currency pairs were transmitters of spillovers. Gold emerged as an attractive investment during periods of inflation or currency devaluation. However, the assets have a total connectedness index of 28.37%, offering a reduced systemic risk. Distinct patterns were observed in the short, medium, and long term in time scales and frequency. There is a diversification benefit and potential hedging strategies due to gold’s negative influence on BTC/ZAR. Bitcoin’s high volatility and lack of regulatory oversight continue to be deterrents for institutional investors. This study lays a solid foundation for understanding the financial dynamics in South Africa, offering valuable insights for investors and policymakers interested in the intricate linkages between BTC/ZAR, currency pairs, and traditional financial assets, allowing for more targeted policy measures.

Suggested Citation

  • Benjamin Mudiangombe Mudiangombe & John Weirstrass Muteba Mwamba, 2025. "Integration and Risk Transmission Dynamics Between Bitcoin, Currency Pairs, and Traditional Financial Assets in South Africa," Econometrics, MDPI, vol. 13(3), pages 1-30, September.
  • Handle: RePEc:gam:jecnmx:v:13:y:2025:i:3:p:36-:d:1753336
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/13/3/36/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2225-1146/13/3/36/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pukthuanthong, Kuntara & Roll, Richard, 2009. "Global market integration: An alternative measure and its application," Journal of Financial Economics, Elsevier, vol. 94(2), pages 214-232, November.
    2. Hoque, Mohammad Enamul & Soo-Wah, Low & Tiwari, Aviral Kumar & Akhter, Tahmina, 2023. "Time and frequency domain connectedness and spillover among categorical and regional financial stress, gold and bitcoin market," Resources Policy, Elsevier, vol. 85(PA).
    3. Muhammad Abubakr Naeem & Saqib Farid & Faruk Balli & Syed Jawad Hussain Shahzad, 2021. "Hedging the downside risk of commodities through cryptocurrencies," Applied Economics Letters, Taylor & Francis Journals, vol. 28(2), pages 153-160, January.
    4. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    5. Shafique Ur Rehman & Touqeer Ahmad & Wu Dash Desheng & Amirhossein Karamoozian, 2024. "Analyzing selected cryptocurrencies spillover effects on global financial indices: Comparing risk measures using conventional and eGARCH-EVT-Copula approaches," Papers 2407.15766, arXiv.org.
    6. George Milunovich, 2018. "Cryptocurrencies, Mainstream Asset Classes and Risk Factors: A Study of Connectedness," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 51(4), pages 551-563, December.
    7. Thabani Ndlovu & Delson Chikobvu, 2023. "A Wavelet-Decomposed WD-ARMA-GARCH-EVT Model Approach to Comparing the Riskiness of the BitCoin and South African Rand Exchange Rates," Data, MDPI, vol. 8(7), pages 1-24, July.
    8. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other assets during bear and bull markets," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5935-5949, November.
    9. Wang, Pengfei & Zhang, Wei & Li, Xiao & Shen, Dehua, 2019. "Is cryptocurrency a hedge or a safe haven for international indices? A comprehensive and dynamic perspective," Finance Research Letters, Elsevier, vol. 31(C), pages 1-18.
    10. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    11. Sebastião, Helder & Godinho, Pedro, 2020. "Bitcoin futures: An effective tool for hedging cryptocurrencies," Finance Research Letters, Elsevier, vol. 33(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bein, Murad A., 2026. "Dynamic interrelations and the potential of global industrial sectors to function as a refuge for the global transition towards a low-carbon economy," The North American Journal of Economics and Finance, Elsevier, vol. 81(C).

    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. Mo, Bin & Meng, Juan & Zheng, Liping, 2022. "Time and frequency dynamics of connectedness between cryptocurrencies and commodity markets," Resources Policy, Elsevier, vol. 77(C).
    2. Ahmed, Walid M.A., 2021. "Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    3. Zhang, Chuanhai & Ma, Huan & Arkorful, Gideon Bruce & Peng, Zhe, 2023. "The impacts of futures trading on volatility and volatility asymmetry of Bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    4. Lucey, Brian & Ren, Boru, 2023. "Time-varying tail risk connectedness among sustainability-related products and fossil energy investments," Energy Economics, Elsevier, vol. 126(C).
    5. Seyram Pearl Kumah & Jones Odei Mensah, 2022. "Are cryptocurrencies connected to gold? A wavelet‐based quantile‐in‐quantile approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3640-3659, July.
    6. Souhir, Ben Amor & Heni, Boubaker & Lotfi, Belkacem, 2019. "Price risk and hedging strategies in Nord Pool electricity market evidence with sector indexes," Energy Economics, Elsevier, vol. 80(C), pages 635-655.
    7. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    8. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
    9. José Almeida & Tiago Cruz Gonçalves, 2024. "Cryptocurrency market microstructure: a systematic literature review," Annals of Operations Research, Springer, vol. 332(1), pages 1035-1068, January.
    10. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    11. Wang, Yu-Min & Lin, Che-Chun & Tsai, I-Chun, 2023. "State transformation of information spillover in asset markets and effective dynamic hedging strategies," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Ren, Boru & Lucey, Brian, 2022. "A clean, green haven?—Examining the relationship between clean energy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 109(C).
    13. Kumah, Seyram Pearl & Odei-Mensah, Jones, 2021. "Are Cryptocurrencies and African stock markets integrated?," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 330-341.
    14. Qiang Ji & Ronald D. Ripple & Dayong Zhang & Yuqian Zhao, 2022. "Cryptocurrency Bubble on the Systemic Risk in Global Energy Companies," The Energy Journal, , vol. 43(1_suppl), pages 1-24, June.
    15. Shahzad, Syed Jawad Hussain & Balli, Faruk & Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad, 2022. "Do conventional currencies hedge cryptocurrencies?," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 223-228.
    16. Sharif, Arshian & Brahim, Mariem & Dogan, Eyup & Tzeremes, Panayiotis, 2023. "Analysis of the spillover effects between green economy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    17. Ahmed, Walid M.A. & Al Mafrachi, Mustafa, 2021. "Do higher-order realized moments matter for cryptocurrency returns?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 483-499.
    18. Patra, Saswat & Singh, Abhay Kumar, 2025. "The impact of financial stress and equity market uncertainty on cryptocurrencies under structural breaks," International Review of Economics & Finance, Elsevier, vol. 101(C).
    19. Hoque, Mohammad Enamul & Billah, Mabruk & Alam, Md Rafayet & Tiwari, Aviral Kumar, 2024. "Gold-backed cryptocurrencies: A hedging tool against categorical and regional financial stress," Global Finance Journal, Elsevier, vol. 60(C).
    20. Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jecnmx:v:13:y:2025:i:3:p:36-:d:1753336. 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.