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Don't miss out on NFTs?! A sentiment-based analysis of the early NFT market

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  • Horky, Florian
  • Dubbick, Lili
  • Rhein, Franziska
  • Fidrmuc, Jarko

Abstract

This study investigates the impact of Twitter sentiment on the Non-Fungible Token (NFT) market. Using a dataset of over 5 million English-language tweets on NFTs, we calculate a daily sentiment index and link it to NFT sales and trading volume. Applying wavelet analysis and DCC-GJR-GARCH models, we analyze the NFT market, characterized by multiple bubbles and high volatility. The findings reveal Twitter's significance as a primary source of information for a broad audience. Moreover, the study contributes to the literature by examining the role of Twitter sentiment in the NFT market's development. Additionally, the study indicates weak links between established cryptocurrencies and the NFT market. Based on our findings, we recommend that traders and policymakers use social media activities to monitor new digital markets.

Suggested Citation

  • Horky, Florian & Dubbick, Lili & Rhein, Franziska & Fidrmuc, Jarko, 2023. "Don't miss out on NFTs?! A sentiment-based analysis of the early NFT market," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 799-814.
    • Handle: RePEc:eee:reveco:v:88:y:2023:i:c:p:799-814
    DOI: 10.1016/j.iref.2023.07.016
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    References listed on IDEAS

    as
    1. Florian Horky & Mihai Mutascu & Jarko Fidrmuc, 2021. "Pandemic Versus Financial Shocks: Comparison of Two Episodes on the Bitcoin Market," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 67(2), pages 113-141.
    2. Mokni, Khaled & Bouteska, Ahmed & Nakhli, Mohamed Sahbi, 2022. "Investor sentiment and Bitcoin relationship: A quantile-based analysis," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    3. Belk, Russell & Humayun, Mariam & Brouard, Myriam, 2022. "Money, possessions, and ownership in the Metaverse: NFTs, cryptocurrencies, Web3 and Wild Markets," Journal of Business Research, Elsevier, vol. 153(C), pages 198-205.
    4. Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
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    Cited by:

    1. Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García-Rubio, Noelia, 2024. "Reflections of public perception of Russia-Ukraine conflict and Metaverse on the financial outlook of Metaverse coins: Fresh evidence from Reddit sentiment analysis," International Review of Financial Analysis, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    NFTs; Digital finance; Crypto markets; Sentiments; Social media activity;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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