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Twitter-Based uncertainty and cryptocurrency returns

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  • Aharon, David Y.
  • Demir, Ender
  • Lau, Chi Keung Marco
  • Zaremba, Adam

Abstract

We explore the relationship between two novel Twitter-based measures of economic and market uncertainty and the performance of four major cryptocurrencies. Using a battery of methods—quantile regressions, Granger-causality in distributions using copula functions, and directional predictability tests—we examine the behavior of Bitcoin, Ethereum, Bitcoin Cash, and Ripple. Our findings demonstrate a strong causal link between the uncertainty expressed in social media and cryptocurrency returns. The effect is particularly evident for Bitcoin and in the tails of return distributions. Our results cast new light on the importance of cryptocurrencies as an alternative asset class in the wake of global uncertainty.

Suggested Citation

  • Aharon, David Y. & Demir, Ender & Lau, Chi Keung Marco & Zaremba, Adam, 2022. "Twitter-Based uncertainty and cryptocurrency returns," Research in International Business and Finance, Elsevier, vol. 59(C).
    • Handle: RePEc:eee:riibaf:v:59:y:2022:i:c:s0275531921001677
    DOI: 10.1016/j.ribaf.2021.101546
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    19. Ivanovski, Kris & Hailemariam, Abebe, 2023. "Forecasting the stock-cryptocurrency relationship: Evidence from a dynamic GAS model," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 97-111.
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    24. Zhang, Jiahang & Zhang, Chi, 2022. "Do cryptocurrency markets react to issuer sentiments? Evidence from Twitter," Research in International Business and Finance, Elsevier, vol. 61(C).

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    More about this item

    Keywords

    Uncertainty; Twitter; Cryptocurrency; Bitcoin; Quantile-in-quantile; Directional test; Granger-causality; Copula;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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