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Emoji Driven Crypto Assets Market Reactions

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  • Xiaorui Zuo
  • Yao-Tsung Chen
  • Wolfgang Karl Hardle

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 like BTC Price and the VCRIX index. 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 analyses into financial strategies, offering a nuanced perspective on the interplay between digital communication and market dynamics in an academic context.

Suggested Citation

  • Xiaorui Zuo & Yao-Tsung Chen & Wolfgang Karl Hardle, 2024. "Emoji Driven Crypto Assets Market Reactions," Papers 2402.10481, arXiv.org.
    • Handle: RePEc:arx:papers:2402.10481
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    References listed on IDEAS

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    1. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    2. 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.
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