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Stablecoins as anchors? Unraveling information flow dynamics between pegged and unpegged crypto-assets and fiat currencies

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  • Palazzi, Rafael Baptista
  • Schich, Sebastian
  • de Genaro, Alan

Abstract

This study empirically investigates the potential of stablecoins to act as anchors within the volatile cryptocurrency market, using a novel conceptual framework that defines an anchor asset in three dimensions relative to other assets, namely stability, independence, and resilience. To assess these three dimensions, we employ three distinct methods to analyze the linear and nonlinear relationships between stablecoins (Tether, USD Coin, and Binance USD), the top three unpegged crypto-assets (Bitcoin, Ethereum, and Binance), and the three most heavily traded fiat currencies after the US dollar (EUR, JPY, and GBP), all denominated in USD. Specifically, we utilize Granger causality, asymmetric dynamic conditional correlation (ADCC)-GARCH, and transfer entropy approaches. These methods help us examine volatility spillover effects among the three types of assets. Our resilience criteria requires us to measure market liquidity, which we do by employing the turnover ratio weighted by market capitalization and the approach proposed by Abdi and Ranaldo (2017). The results challenge the notion that stablecoins are robust anchors in the sense that they are more stable, independent, or resilient than other types of assets, and cast doubt on the suggestion that stablecoins might become a useful means of exchange that provide a private alternative to existing fiat currencies.

Suggested Citation

  • Palazzi, Rafael Baptista & Schich, Sebastian & de Genaro, Alan, 2025. "Stablecoins as anchors? Unraveling information flow dynamics between pegged and unpegged crypto-assets and fiat currencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 99(C).
  • Handle: RePEc:eee:intfin:v:99:y:2025:i:c:s1042443124001744
    DOI: 10.1016/j.intfin.2024.102108
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    Keywords

    Stablecoins; Transfer entropy; Fiat currencies; Cryptoassets; Anchor;
    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
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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