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Beyond the hype: examining the relationship between Wikipedia attention and realised skewness for crypto assets

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  • Kingstone Nyakurukwa

    (University of the Witwatersrand)

  • Yudhvir Seetharam

    (University of the Witwatersrand)

Abstract

This study investigates the relationship between Wikipedia searches and the next day’s realised skewness for the top four cryptocurrencies between 2020 and 2022, using a time-varying framework. Daily realised skewness was calculated using one-minute data, and Wikipedia queries were used as a proxy for investor attention. The study reports a positive time-varying relationship between today’s Wikipedia attention and the next day’s realised skewness, with increases in Wikipedia attention on a given day associated with higher realised skewness on the following day. However, there was no significant contemporaneous relationship between Wikipedia attention and realised skewness. The study also found that the relationship between Wikipedia attention and realised skewness becomes more stable over time. The findings suggest that Wikipedia attention may be a useful predictor of realised skewness for cryptocurrencies, which could have implications for investors and market participants.

Suggested Citation

  • Kingstone Nyakurukwa & Yudhvir Seetharam, 2023. "Beyond the hype: examining the relationship between Wikipedia attention and realised skewness for crypto assets," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-12, September.
    • Handle: RePEc:pal:risman:v:25:y:2023:i:3:d:10.1057_s41283-023-00124-2
    DOI: 10.1057/s41283-023-00124-2
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    1. Caldara, Dario & Fuentes-Albero, Cristina & Gilchrist, Simon & Zakrajšek, Egon, 2016. "The macroeconomic impact of financial and uncertainty shocks," European Economic Review, Elsevier, vol. 88(C), pages 185-207.
    2. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    3. Amaya, Diego & Christoffersen, Peter & Jacobs, Kris & Vasquez, Aurelio, 2015. "Does realized skewness predict the cross-section of equity returns?," Journal of Financial Economics, Elsevier, vol. 118(1), pages 135-167.
    4. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    5. Yao, Shouyu & Wang, Chunfeng & Cui, Xin & Fang, Zhenming, 2019. "Idiosyncratic skewness, gambling preference, and cross-section of stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 464-483.
    6. Markus K. Brunnermeier & Jonathan A. Parker & Christian Gollier, 2007. "Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns," American Economic Review, American Economic Association, vol. 97(2), pages 159-165, May.
    7. Abeer ElBahrawy & Laura Alessandretti & Andrea Baronchelli, 2019. "Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performance," Papers 1902.04517, arXiv.org, revised Mar 2019.
    8. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    9. Lin, Chiao-Han & Yen, Kuang-Chieh & Cheng, Hui-Pei, 2021. "Lottery-like momentum in the cryptocurrency market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    10. Sowmya Subramaniam & Madhumita Chakraborty, 2020. "Investor Attention and Cryptocurrency Returns: Evidence from Quantile Causality Approach," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 21(1), pages 103-115, January.
    11. Wei Zhang & Pengfei Wang, 2020. "Investor attention and the pricing of cryptocurrency market," Evolutionary and Institutional Economics Review, Springer, vol. 17(2), pages 445-468, July.
    12. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    13. Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa & Wang, Yizhi, 2022. "The cryptocurrency uncertainty index," Finance Research Letters, Elsevier, vol. 45(C).
    14. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    15. Imene Ben El Hadj Said & Skander Slim, 2022. "The Dynamic Relationship between Investor Attention and Stock Market Volatility: International Evidence," JRFM, MDPI, vol. 15(2), pages 1-25, February.
    16. Yukun Liu & Aleh Tsyvinski, 2021. "Risks and Returns of Cryptocurrency," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 2689-2727.
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    Cited by:

    1. Pyun, Chaehyun, 2024. "The Wikipedia effect: Analyzing investor attention for strategic investment decisions," Economics Letters, Elsevier, vol. 241(C).

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