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Cross-market volatility dynamics in crypto and traditional financial instruments: quantifying the spillover effect

Author

Listed:
  • Mohamad H. Shahrour
  • Ryan Lemand
  • Mathis Mourey

Abstract

Purpose - This paper examines the volatility spillover effects from traditional financial assets to cryptocurrency markets and vice versa. It aims to provide insights into the dynamic interconnectedness of these markets. Design/methodology/approach - This paper employs the time-varying parameter vector autoregression technique to examine the volatility spillover among the crypto markets (across leading cryptocurrencies such as Bitcoin (BTC), USD Tether, NEAR Protocol (NEAR), Immutable and Dogecoin) and traditional financial instruments (Treasury Bills (TBILL) and Volatility Index). Findings - The results reveal significant bidirectional volatility spillovers between cryptocurrencies and traditional financial assets. NEAR and BTC act as a major transmitter of volatility, both influencing others significantly (71.63 and 68.17%, respectively) and being influenced by others (54.74 and 62.3%, respectively). TBILL and Grayscale Bitcoin Trust ETF are the largest net receivers of volatility, indicating a higher dependency on other assets’ volatility. Practical implications - Understanding the volatility spillover dynamics can aid investors in portfolio diversification and risk management. The findings provide actionable insights for constructing portfolios that include both cryptocurrencies and traditional financial assets, allowing for more informed investment decisions under volatile market conditions. Originality/value - This paper contributes to the literature by analyzing volatility spillovers among traditional financial markets and various major cryptocurrencies. It offers a framework for assessing how shocks in one market or cryptocurrency can propagate to others, thereby enhancing the understanding of interconnectedness between markets. This understanding improves our ability to risk manage modern portfolios, which increasingly include significant alternative assets like cryptocurrencies.

Suggested Citation

  • Mohamad H. Shahrour & Ryan Lemand & Mathis Mourey, 2024. "Cross-market volatility dynamics in crypto and traditional financial instruments: quantifying the spillover effect," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 26(1), pages 1-21, December.
  • Handle: RePEc:eme:jrfpps:jrf-07-2024-0185
    DOI: 10.1108/JRF-07-2024-0185
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    More about this item

    Keywords

    Volatility spillover; Cryptocurrencies; Interconnectedness; Risk management; Portfolio diversification; C22; C32; E44;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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