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Asymmetric tail dependence in cryptocurrency markets: A Model-free approach

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  • Ahn, Yongkil

Abstract

This paper investigates extreme tail dependence between cryptocurrencies and the S&P 500 index using a model-free approach. It appears that any symmetric model fails to explain the correlation structure in major cryptocurrency returns. Moreover, the sample downward tail correlations between cryptocurrencies and the equity market are much greater than the upward tail ones. The disadvantages of cryptocurrencies as an asset class might be more lively because cryptocurrencies entail high asymmetric tail dependence, especially when the equity market is going down.

Suggested Citation

  • Ahn, Yongkil, 2022. "Asymmetric tail dependence in cryptocurrency markets: A Model-free approach," Finance Research Letters, Elsevier, vol. 47(PB).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pb:s1544612322000666
    DOI: 10.1016/j.frl.2022.102746
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    References listed on IDEAS

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    Cited by:

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    2. Ahn, Jungkyu & Ahn, Yongkil, 2022. "Demystifying the US Treasury floating rate note puzzle: A swap market perspective," Finance Research Letters, Elsevier, vol. 50(C).
    3. Bouri, Elie & Kamal, Elham & Kinateder, Harald, 2023. "FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies," Finance Research Letters, Elsevier, vol. 56(C).
    4. Nagl, Maximilian, 2024. "Intricacy of cryptocurrency returns," Economics Letters, Elsevier, vol. 239(C).
    5. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    6. Yousaf, Imran & Pham, Linh & Goodell, John W., 2023. "Interconnectedness between healthcare tokens and healthcare stocks: Evidence from a quantile VAR approach," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 271-283.
    7. Cao, Guangxi & Xie, Wenhao, 2022. "Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: Evidence from TVP-VAR based connectedness approach," Finance Research Letters, Elsevier, vol. 49(C).
    8. Chen, Yan & Liu, Yakun & Zhang, Feipeng, 2024. "Coskewness and the short-term predictability for Bitcoin return," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    9. Xia, Yufei & Li, Jinglong & Fu, Yating, 2022. "Are non-fungible tokens (NFTs) different asset classes? Evidence from quantile connectedness approach," Finance Research Letters, Elsevier, vol. 49(C).

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    More about this item

    Keywords

    Extreme tail dependence; Cryptocurrency; Asymmetric correlation;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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