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Bridging the gap: Uncovering static and dynamic relationships between digital assets and BRICS equity markets

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  • Ali, Shoaib
  • Al-Nassar, Nassar S.
  • Naveed, Muhammad

Abstract

This study uniquely explores the link between nonfungible tokens (NFTs) and the stock markets, providing vital insights for investors to optimize portfolios during global uncertainties such as the health crisis and geopolitical conflicts. We employ the quantile vector autoregression (QVAR) model on daily data from March 14, 2018 to December 23, 2022. Subsequently, the statistics for portfolio analysis are computed using the DCC-GARCH model. Our results highlight that total connectedness at both extremes is significantly higher than at the mean and median quantiles suggesting strong impact of extreme events. The findings reveal that the equity markets of the BRICS countries receive shocks from the system, and NFTs act as transmitters of these shocks. Finally, the pre-COVID-19 pandemic optimal weights remained lower than the COVID-19 pandemic weights, proposing that to reduce risk investors should increase investment in BRICS markets. Similarly, the higher hedge ratio during the turmoil period implies a higher hedging cost. Our findings imply that investors should consider adjusting their investment strategies during periods of heightened global uncertainty to minimize risk and maximize returns.

Suggested Citation

  • Ali, Shoaib & Al-Nassar, Nassar S. & Naveed, Muhammad, 2024. "Bridging the gap: Uncovering static and dynamic relationships between digital assets and BRICS equity markets," Global Finance Journal, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:glofin:v:60:y:2024:i:c:s1044028324000279
    DOI: 10.1016/j.gfj.2024.100955
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    More about this item

    Keywords

    Digital assets; Nonfungible tokens; BRICS; COVID-19; Russia–Ukraine conflict; Portfolios;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F3 - International Economics - - International Finance
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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