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Higher moments, extreme returns, and cross–section of cryptocurrency returns

Author

Listed:
  • Jia, Yuecheng
  • Liu, Yuzheng
  • Yan, Shu

Abstract

This study examines the cross–sectional return predictability of the higher moments of 84 cryptocurrencies computed using intraday data. We document strong evidence that volatility and kurtosis are positively related to future returns while the return predictability of skewness is negative. Further analysis indicates that the extreme positive returns but not the extreme negative returns significantly impact the return predictability of higher moments. The evidence implies that cryptocurrency investors have lottery–type preferences and are not concerned much about crash risk.

Suggested Citation

  • Jia, Yuecheng & Liu, Yuzheng & Yan, Shu, 2021. "Higher moments, extreme returns, and cross–section of cryptocurrency returns," Finance Research Letters, Elsevier, vol. 39(C).
    • Handle: RePEc:eee:finlet:v:39:y:2021:i:c:s1544612320303135
    DOI: 10.1016/j.frl.2020.101536
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    References listed on IDEAS

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    1. Zhao, Xiaojuan & Wang, Ye & Liu, Weiyi, 2024. "Someone like you: Lottery-like preference and the cross-section of expected returns in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    2. Milan Fičura, 2023. "Impact of size and volume on cryptocurrency momentum and reversal," FFA Working Papers 5.003, Prague University of Economics and Business, revised 05 Apr 2023.
    3. Liebi, Luca J., 2022. "Is there a value premium in cryptoasset markets?," Economic Modelling, Elsevier, vol. 109(C).
    4. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    5. Long, Huaigang & Demir, Ender & Będowska-Sójka, Barbara & Zaremba, Adam & Shahzad, Syed Jawad Hussain, 2022. "Is geopolitical risk priced in the cross-section of cryptocurrency returns?," Finance Research Letters, Elsevier, vol. 49(C).
    6. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
    7. Fieberg, Christian & Liedtke, Gerrit & Zaremba, Adam, 2024. "Cryptocurrency anomalies and economic constraints," International Review of Financial Analysis, Elsevier, vol. 94(C).
    8. 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.
    9. Bouri, Elie & Jalkh, Naji, 2023. "Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. Böyükaslan, Adem & Ecer, Fatih, 2021. "Determination of drivers for investing in cryptocurrencies through a fuzzy full consistency method-Bonferroni (FUCOM-F’B) framework," Technology in Society, Elsevier, vol. 67(C).
    11. Waqas Hanif & Hee-Un Ko & Linh Pham & Sang Hoon Kang, 2023. "Dynamic connectedness and network in the high moments of cryptocurrency, stock, and commodity markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    12. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    13. Yang, Jen-Wei & Chiu, Shih-Yung & Yen, Kuang-Chieh, 2023. "Does the realized distribution-based measure dominate particular moments? Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    14. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2023. "Multivariate dynamics between emerging markets and digital asset markets: An application of the SNP-DCC model," Emerging Markets Review, Elsevier, vol. 56(C).
    15. Esparcia, Carlos & López, Raquel, 2024. "Performance of crypto-Forex portfolios based on intraday data," Research in International Business and Finance, Elsevier, vol. 69(C).

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    More about this item

    Keywords

    Cryptocurrency; Return; Volatility; Skewness; Kurtosis; Extreme returns; Lottery preference; Crash risk;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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