IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2312.05346.html
   My bibliography  Save this paper

Deep Learning for Dynamic NFT Valuation

Author

Listed:
  • Mingxuan He

Abstract

I study the price dynamics of non-fungible tokens (NFTs) and propose a deep learning framework for dynamic valuation of NFTs. I use data from the Ethereum blockchain and OpenSea to train a deep learning model on historical trades, market trends, and traits/rarity features of Bored Ape Yacht Club NFTs. After hyperparameter tuning, the model is able to predict the price of NFTs with high accuracy. I propose an application framework for this model using zero-knowledge machine learning (zkML) and discuss its potential use cases in the context of decentralized finance (DeFi) applications.

Suggested Citation

  • Mingxuan He, 2023. "Deep Learning for Dynamic NFT Valuation," Papers 2312.05346, arXiv.org.
    • Handle: RePEc:arx:papers:2312.05346
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2312.05346
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting NFT coin prices using machine learning: Insights into feature significance and portfolio strategies," Global Finance Journal, Elsevier, vol. 58(C).
    2. Horky, Florian & Rachel, Carolina & Fidrmuc, Jarko, 2022. "Price determinants of non-fungible tokens in the digital art market," Finance Research Letters, Elsevier, vol. 48(C).
    3. Amin Mekacher & Alberto Bracci & Matthieu Nadini & Mauro Martino & Laura Alessandretti & Luca Maria Aiello & Andrea Baronchelli, 2022. "Heterogeneous rarity patterns drive price dynamics in NFT collections," Papers 2204.10243, arXiv.org, revised Aug 2022.
    4. Lennart Ante, 2022. "The Non-Fungible Token (NFT) Market and Its Relationship with Bitcoin and Ethereum," FinTech, MDPI, vol. 1(3), pages 1-9, June.
    5. Laura Alessandretti & Abeer ElBahrawy & Luca Maria Aiello & Andrea Baronchelli, 2018. "Anticipating cryptocurrency prices using machine learning," Papers 1805.08550, arXiv.org, revised Nov 2018.
    6. Matthieu Nadini & Laura Alessandretti & Flavio Di Giacinto & Mauro Martino & Luca Maria Aiello & Andrea Baronchelli, 2021. "Mapping the NFT revolution: market trends, trade networks and visual features," Papers 2106.00647, arXiv.org, revised Sep 2021.
    7. Dowling, Michael, 2022. "Is non-fungible token pricing driven by cryptocurrencies?," Finance Research Letters, Elsevier, vol. 44(C).
    8. Shrey Jain & Camille Bruckmann & Chase McDougall, 2022. "NFT Appraisal Prediction: Utilizing Search Trends, Public Market Data, Linear Regression and Recurrent Neural Networks," Papers 2204.12932, arXiv.org.
    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. Zhang, Luyao & Sun, Yutong & Quan, Yutong & Cao, Jiaxun & Tong, Xin, 2023. "On the Mechanics of NFT Valuation: AI Ethics and Social Media," OSF Preprints qwpdx, Center for Open Science.
    2. Fridgen, Gilbert & Kräussl, Roman & Papageorgiou, Orestis & Tugnetti, Alessandro, 2023. "The fundamental value of art NFTs," CFS Working Paper Series 709, Center for Financial Studies (CFS).
    3. Ewelina Plachimowicz & Piotr Wójcik, 2022. "What makes Punks worthy? Valuation of Non-Fungible Tokens based on the CryptoPunks collection using the hedonic pricing method," Working Papers 2022-27, Faculty of Economic Sciences, University of Warsaw.
    4. Proelss, Juliane & Sévigny, Stéphane & Schweizer, Denis, 2023. "GameFi: The perfect symbiosis of blockchain, tokens, DeFi, and NFTs?," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Ozge Camalan & Sahika Gokmen & Sibel Atan, 2024. "Using Advanced Machine Learning Techniques to Predict the Sales Volume of Non-Fungible Tokens," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 10(1), pages 17-27, June.
    6. Ghosh, Bikramaditya & Bouri, Elie & Wee, Jung Bum & Zulfiqar, Noshaba, 2023. "Return and volatility properties: Stylized facts from the universe of cryptocurrencies and NFTs," Research in International Business and Finance, Elsevier, vol. 65(C).
    7. Wang, Yizhi, 2022. "Volatility spillovers across NFTs news attention and financial markets," International Review of Financial Analysis, Elsevier, vol. 83(C).
    8. Bao, Te & Ma, Mengzhong & Wen, Yonggang, 2023. "Herding in the non-fungible token (NFT) market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    9. Chong Guan & Ding Ding & Jing Ren & Jiancang Guo, 2024. "Unveiling the aesthetic “wow factor”: The role of aesthetic incongruity and image quality in NFT art valuation with computer vision," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-16, December.
    10. Umar, Zaghum & Usman, Muhammad & Choi, Sun-Yong & Rice, John, 2023. "Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios," Research in International Business and Finance, Elsevier, vol. 65(C).
    11. Choi, Jaeseo, 2024. "A Study on the Applicability of NFT in the Entertainment Industry: Application of the Means-end Chain analysis and Laddering," 24th ITS Biennial Conference, Seoul 2024. New bottles for new wine: digital transformation demands new policies and strategies 302456, International Telecommunications Society (ITS).
    12. Wang, Jying-Nan & Lee, Yen-Hsien & Liu, Hung-Chun & Hsu, Yuan-Teng, 2023. "Dissecting returns of non-fungible tokens (NFTs): Evidence from CryptoPunks," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    13. Theodore Panagiotidis & Georgios Papapanagiotou, 2024. "A note on the determinants of NFTs returns," Working Paper series 24-07, Rimini Centre for Economic Analysis.
    14. Andrea Barbon & Angelo Ranaldo, 2023. "NFT Bubbles," Swiss Finance Institute Research Paper Series 23-20, Swiss Finance Institute.
    15. An, Jaehyung & Mikhaylov, Alexey & Chang, Tsangyao, 2024. "Relationship between the popularity of a platform and the price of NFT assets," Finance Research Letters, Elsevier, vol. 61(C).
    16. Ali, Shoaib & Al-Nassar, Nassar S. & Naveed, Muhammad, 2024. "Bridging the gap: Uncovering static and dynamic relationships between digital assets and BRICS equity markets," Global Finance Journal, Elsevier, vol. 60(C).
    17. Niklas Konstantin Klein & Fritz Lattermann & Dirk Schiereck, 2023. "Investment in non-fungible tokens (NFTs): the return of Ethereum secondary market NFT sales," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 241-254, July.
    18. Chih-Hung Wu & Chien-Yu Liu & Ting-Sheng Weng, 2023. "Critical Factors and Trends in NFT Technology Innovations," Sustainability, MDPI, vol. 15(9), pages 1-25, May.
    19. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "Dynamic connectedness between non-fungible tokens, decentralized finance, and conventional financial assets in a time-frequency framework," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    20. Kensuke Ito, 2024. "Cryptoeconomics and Tokenomics as Economics: A Survey with Opinions," Papers 2407.15715, arXiv.org.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2312.05346. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.