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Investor attention and cryptocurrency performance

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  • Lin, Zih-Ying

Abstract

This paper investigates the causal relation between the performance of several cryptocurrencies and investor attention by employing Granger Causality tests and Vector Autoregression (VAR) models to examine such a relation. The findings show that interaction effects exist between returns and attention when I use Granger Causality tests, but when using VAR models, past cryptocurrency returns present a significant effect on future attention and weak reverse results. Thus, I hypothesize that if a cryptocurrency has higher past performance, then investors may pay more attention to it. After controlling the effect of economy-wide variables, I still find that past cryptocurrency returns significantly impact future attention.

Suggested Citation

  • Lin, Zih-Ying, 2021. "Investor attention and cryptocurrency performance," Finance Research Letters, Elsevier, vol. 40(C).
    • Handle: RePEc:eee:finlet:v:40:y:2021:i:c:s1544612320306590
    DOI: 10.1016/j.frl.2020.101702
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    Cited by:

    1. Kamal, Javed Bin & Hassan, M. Kabir, 2022. "Asymmetric connectedness between cryptocurrency environment attention index and green assets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
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    3. Maher Abida & Emna Mnif, 2023. "Investor Attention in Cryptocurrency Markets: Examining the Effects of Vaccination and COVID-19 Spread through a Wavelet Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 13(5), pages 43-51, September.
    4. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    5. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    6. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    7. Nguyen, Khanh Quoc & Nguyen, Thanh Huong & Do, Bao Linh, 2023. "Narrative attention and related cryptocurrency returns," Finance Research Letters, Elsevier, vol. 56(C).
    8. Bouteska, Ahmed & Mefteh-Wali, Salma & Dang, Trung, 2022. "Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    9. Caferra, Rocco, 2022. "Sentiment spillover and price dynamics: Information flow in the cryptocurrency and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    10. Rasoul Amirzadeh & Asef Nazari & Dhananjay Thiruvady & Mong Shan Ee, 2023. "Modelling Determinants of Cryptocurrency Prices: A Bayesian Network Approach," Papers 2303.16148, arXiv.org.
    11. Florentina Șoiman & Jean-Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX [Le rendement de (I)DeFiX]," Working Papers hal-03625891, HAL.
    12. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
    13. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    14. Florentina c{S}oiman & Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX," Papers 2204.00251, arXiv.org.

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    More about this item

    Keywords

    Investor attention; Cryptocurrency returns; Google search probability; Vector autoregression;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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