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Frequency domain causality and quantile connectedness between investor sentiment and cryptocurrency returns

Author

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  • Zhu, Huiming
  • Xing, Zhanming
  • Ren, Yinghua
  • Chen, Yiwen
  • Hau, Liya

Abstract

This study investigates the frequency-domain causality and quantile connectedness between online investors’ fear sentiment and cryptocurrency returns. We propose cross-quantile coherency and networks to examine the frequency-domain nonlinear interdependence. First, we find that investor fear sentiment and cryptocurrency returns exhibit bidirectional causality. Second, fear exhibits an asymmetric connectedness with cryptocurrency returns across quantiles and frequencies. Third, short-term cross-quantile connectedness is found to be more significant than long-term connectedness. These findings can help investors and policymakers make decisions regarding diversified hedging and controlling for potential risks.

Suggested Citation

  • Zhu, Huiming & Xing, Zhanming & Ren, Yinghua & Chen, Yiwen & Hau, Liya, 2023. "Frequency domain causality and quantile connectedness between investor sentiment and cryptocurrency returns," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1035-1051.
    • Handle: RePEc:eee:reveco:v:88:y:2023:i:c:p:1035-1051
    DOI: 10.1016/j.iref.2023.07.038
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    Cited by:

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    2. Binlin Li & Nils Haneklaus & Mohammad Mafizur Rahman, 2024. "Dynamic connectedness and hedging opportunities of the commodity and stock markets in China: evidence from the TVP-VAR and cDCC-FIAPARCH," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-30, December.
    3. Abakah, Emmanuel Joel Aikins & Brahim, Mariem & Carlotti, Jean-Etienne & Tiwari, Aviral Kumar & Mensi, Walid, 2024. "Extreme downside risk connectedness and portfolio hedging among the G10 currencies," International Economics, Elsevier, vol. 178(C).

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    More about this item

    Keywords

    Investor sentiment; Fears; Cryptocurrency returns; Frequency domain causality; Cross-quantile coherency; Cross-quantile network;
    All these keywords.

    JEL classification:

    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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