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Dependence in cryptocurrencies: A Partial correlation connectedness approach

Author

Listed:
  • Shen, Yijuan
  • Li, Zecheng
  • Yuan, Yuan
  • Cai, Yifei

Abstract

This study investigates the connectedness among eleven cryptocurrencies using partial correlation and generalized forecast variance decomposition (GFEVD) approaches under normal and extreme market conditions. The results show that the system is highly interconnected overall, with GFEVD based total connectedness remaining persistently high. However, the partial correlation framework reveals stronger nonlinear and downside dependence, with connectedness intensifying markedly dur-ing market downturns. While GFEVD results suggest relatively symmetric spillovers, conditional dependence analysis highlights greater systemic vulnerability under adverse conditions. Finally, pol-icy implications are provided.

Suggested Citation

  • Shen, Yijuan & Li, Zecheng & Yuan, Yuan & Cai, Yifei, 2026. "Dependence in cryptocurrencies: A Partial correlation connectedness approach," Finance Research Letters, Elsevier, vol. 104(C).
    • Handle: RePEc:eee:finlet:v:104:y:2026:i:c:s1544612326007233
    DOI: 10.1016/j.frl.2026.110195
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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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