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Momentum or reversal: Which is the appropriate third factor for cryptocurrencies?

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  • Jia, Boxiang
  • Goodell, John W.
  • Shen, Dehua

Abstract

Shen et al. (2020) propose a three-factor pricing model for cryptocurrencies by including market, size, and reversal factors. However, evidence from cryptocurrencies during a more recent sample period suggests the existence of a momentum effect rather than a reversal effect. Consequently, we introduce and test a three-factor pricing model including market, size, and momentum factors (MSM three-factor model). This MSM three-factor model outperforms the quasi-cryptocurrency CAPM (Q-C-CAPM) of Shen et al. (2020), with greater explanatory power.

Suggested Citation

  • Jia, Boxiang & Goodell, John W. & Shen, Dehua, 2022. "Momentum or reversal: Which is the appropriate third factor for cryptocurrencies?," Finance Research Letters, Elsevier, vol. 45(C).
    • Handle: RePEc:eee:finlet:v:45:y:2022:i:c:s1544612321002208
    DOI: 10.1016/j.frl.2021.102139
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    References listed on IDEAS

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    Cited by:

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    3. Yao, Shouyu & Qin, Yuanyuan & Cheng, Feiyang & Wu, Ji(George) & Goodell, John.W., 2022. "Missing momentum in China: Considering individual investor preference," Finance Research Letters, Elsevier, vol. 49(C).
    4. Li, Bo & Liu, Zhenya & Teka, Hanen & Wang, Shixuan, 2023. "The evolvement of momentum effects in China: Evidence from functional data analysis," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. 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.
    6. 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).
    7. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    8. Wang, Lu & Ruan, Hang & Hong, Yanran & Luo, Keyu, 2023. "Detecting the hidden asymmetric relationship between crude oil and the US dollar: A novel neural Granger causality method," Research in International Business and Finance, Elsevier, vol. 64(C).
    9. Petkova, Ralitsa, 2023. "Extrapolative beliefs about Bitcoin returns," Finance Research Letters, Elsevier, vol. 56(C).
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    11. Adedeji Daniel Gbadebo, 2023. "Dynamic Asymmetric Causality of Bitcoin’s Price-Volume Relation," SAGE Open, , vol. 13(4), pages 21582440231, December.
    12. Wang, Yaqi & Wang, Chunfeng & Sensoy, Ahmet & Yao, Shouyu & Cheng, Feiyang, 2022. "Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning," Research in International Business and Finance, Elsevier, vol. 62(C).

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