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Investor Attention and Cryptocurrency Returns: Evidence from Quantile Causality Approach

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  • Sowmya Subramaniam
  • Madhumita Chakraborty

Abstract

The erratic price behavior and inefficiency in the crypto markets offer possibility to examine the behavioral aspects in cryptocurrency prices. Further, the cryptocurrency market is dominated by the retail investor providing an interesting platform to examine the impact of attention-driven trading in this particular asset class. Thus, the authors investigate the influence of investor attention in the cryptocurrency prices using the quantile causality approach. The results indicate that investors pay attention to the frequent news-making and ranked cryptos (Bitcoin and Ethereum). For newer cryptocurrencies like Ripple, investor attention influences their prices only during superior performance. The study provides evidence of attention-induced price pressure hypothesis in the prices of cryptocurrencies during expansionary phases and fear selling during poor market performance.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:hbhfxx:v:21:y:2020:i:1:p:103-115
    DOI: 10.1080/15427560.2019.1629587
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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).
    2. Saggu, Aman & Ante, Lennart, 2023. "The influence of ChatGPT on artificial intelligence related crypto assets: Evidence from a synthetic control analysis," Finance Research Letters, Elsevier, vol. 55(PB).
    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. Ozdamar, Melisa & Sensoy, Ahmet & Akdeniz, Levent, 2022. "Retail vs institutional investor attention in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    5. Ayadi, Ahmed & Ghabri, Yosra & Guesmi, Khaled, 2023. "Directional predictability from central bank digital currency to cryptocurrencies and stablecoins," Research in International Business and Finance, Elsevier, vol. 65(C).
    6. Anastasiou, Dimitrios & Ballis, Antonis & Drakos, Konstantinos, 2021. "Cryptocurrencies’ Price Crash Risk and Crisis Sentiment," Finance Research Letters, Elsevier, vol. 42(C).
    7. Akyildirim, Erdinc & Aysan, Ahmet Faruk & Cepni, Oguzhan & Darendeli, S. Pinar Ceyhan, 2021. "Do investor sentiments drive cryptocurrency prices?," Economics Letters, Elsevier, vol. 206(C).
    8. 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).
    9. 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.
    10. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    11. Chen, Conghui & Liu, Lanlan, 2022. "How effective is China's cryptocurrency trading ban?," Finance Research Letters, Elsevier, vol. 46(PB).
    12. Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa & Wang, Yizhi, 2022. "The cryptocurrency uncertainty index," Finance Research Letters, Elsevier, vol. 45(C).
    13. Dias, Ishanka K. & Fernando, J.M. Ruwani & Fernando, P. Narada D., 2022. "Does investor sentiment predict bitcoin return and volatility? A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    14. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    15. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis & Corbet, Shaen, 2021. "Herding behaviour and price convergence clubs in cryptocurrencies during bull and bear markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    16. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Saleem, Owais & Adeoye, Habeeb A., 2022. "Asymmetric connectedness between Google-based investor attention and the fourth industrial revolution assets: The case of FinTech and Robotics & Artificial intelligence stocks," Technology in Society, Elsevier, vol. 68(C).
    17. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).
    18. Pham, Linh & Cepni, Oguzhan, 2022. "Extreme directional spillovers between investor attention and green bond markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 186-210.
    19. Zheng, Yan & Wen, Fenghua & Deng, Hanshi & Zeng, Aiqing, 2022. "The relationship between carbon market attention and the EU CET market: Evidence from different market conditions," Finance Research Letters, Elsevier, vol. 50(C).

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