IDEAS home Printed from https://ideas.repec.org/a/vrs/manmar/v19y2024i2p158-178n1001.html
   My bibliography  Save this article

Emoji driven crypto assets market reactions

Author

Listed:
  • Zuo Xiaorui

    (Fudan University, Shanghai, China IDA Institute Digital Assets, Bucharest University of Economic Studies, Bucharest, Romania)

  • Chen Yao-Tsung

    (Department of Information Management and Finance, College of Management, National Yang Ming Chiao Tung University, Hsinchu, Taiwan)

  • Härdle Wolfgang Karl

    (BRC Blockchain Research Center, Humboldt Universität zu Berlin, Berlin, Germany Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic; Dept Information Management and Finance, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; IDA Institute Digital Assets, Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

In the burgeoning realm of cryptocurrency, social media platforms like Twitter have become pivotal in influencing market trends and investor sentiments. In our study, we leverage GPT-4 and a fine-tuned transformer-based BERT model for a multimodal sentiment analysis, focusing on the impact of emoji sentiment on cryptocurrency markets. By translating emojis into quantifiable sentiment data, we correlate these insights with key market indicators such as BTC Price and the VCRIX index. Our architecture’s analysis of emoji sentiment demonstrated a distinct advantage over FinBERT’s pure text sentiment analysis in such predicting power. This approach may be fed into the development of trading strategies aimed at utilizing social media elements to identify and forecast market trends. Crucially, our findings suggest that strategies based on emoji sentiment can facilitate the avoidance of significant market downturns and contribute to the stabilization of returns. This research underscores the practical benefits of integrating advanced AI-driven analyzes into financial strategies, offering a nuanced perspective on the interaction between digital communication and market dynamics in an academic context.

Suggested Citation

  • Zuo Xiaorui & Chen Yao-Tsung & Härdle Wolfgang Karl, 2024. "Emoji driven crypto assets market reactions," Management & Marketing, Sciendo, vol. 19(2), pages 158-178.
    • Handle: RePEc:vrs:manmar:v:19:y:2024:i:2:p:158-178:n:1001
    DOI: 10.2478/mmcks-2024-0008
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/mmcks-2024-0008
    Download Restriction: no
    File URL: https://libkey.io/10.2478/mmcks-2024-0008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Francis Liu & Natalie Packham & Meng-Jou Lu & Wolfgang Karl Härdle, 2023. "Hedging cryptos with Bitcoin futures," Quantitative Finance, Taylor & Francis Journals, vol. 23(5), pages 819-841, May.
    2. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    3. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    4. Ben Osman, Myriam & Galariotis, Emilios & Guesmi, Khaled & Hamdi, Haykel & Naoui, Kamel, 2024. "Are markets sentiment driving the price bubbles in the virtual?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 272-285.
    5. Härdle, Wolfgang Karl & Trimborn, Simon, 2015. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers 2015-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Ai Jun Hou & Weining Wang & Cathy Y H Chen & Wolfgang Karl Härdle, 2020. "Pricing Cryptocurrency Options," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 250-279.
    7. Timm O. Sprenger & Philipp G. Sandner & Andranik Tumasjan & Isabell M. Welpe, 2014. "News or Noise? Using Twitter to Identify and Understand Company-specific News Flow," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(7-8), pages 791-830, September.
    8. Sergey Nasekin & Cathy Yi-Hsuan Chen, 2020. "Deep learning-based cryptocurrency sentiment construction," Digital Finance, Springer, vol. 2(1), pages 39-67, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    2. Lin, Min-Bin & Khowaja, Kainat & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2020. "Blockchain mechanism and distributional characteristics of cryptos," IRTG 1792 Discussion Papers 2020-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Xiaorui Zuo & Yao-Tsung Chen & Wolfgang Karl Hardle, 2024. "Emoji Driven Crypto Assets Market Reactions," Papers 2402.10481, arXiv.org, revised May 2024.
    4. Matic, Jovanka & Packham, Natalie & Härdle, Wolfgang, 2021. "Hedging cryptocurrency options," IRTG 1792 Discussion Papers 2021-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    6. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
    7. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Béatrice BOULU-RESHEF & Catherine BRUNEAU & Maxime NICOLAS & Thomas RENAULT, 2022. "An Experimental Analysis of Investor Sentiment," LEO Working Papers / DR LEO 2940, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    10. Jovanka Lili Matic & Natalie Packham & Wolfgang Karl Härdle, 2023. "Hedging cryptocurrency options," Review of Derivatives Research, Springer, vol. 26(1), pages 91-133, April.
    11. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Hou, Ai Jun & Wang, Weining, 2018. "Pricing Cryptocurrency options: the case of CRIX and Bitcoin," IRTG 1792 Discussion Papers 2018-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    13. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    14. Lee, Seung Jung & Liu, Lucy Qian & Stebunovs, Viktors, 2022. "Risk-taking spillovers of U.S. monetary policy in the global market for U.S. dollar corporate loans," Journal of Banking & Finance, Elsevier, vol. 138(C).
    15. Geert Bekaert & Eric Engstrom, 2017. "Asset Return Dynamics under Habits and Bad Environment-Good Environment Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 713-760.
    16. Lian, Yu-Min & Chen, Jun-Home, 2021. "Pricing virtual currency-linked derivatives with time-inhomogeneity," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 424-439.
    17. Baur, Dirk G. & Smales, Lee A., 2020. "Hedging geopolitical risk with precious metals," Journal of Banking & Finance, Elsevier, vol. 117(C).
    18. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    19. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
    20. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.

    More about this item

    Keywords

    emoji; LLM; VCRIX; crypto; bitcoin;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:manmar:v:19:y:2024:i:2:p:158-178:n:1001. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.