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Picture For Proof(PFPs): Aesthetics, IP and post launch performance

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  • Tian, Yingjie
  • Xie, Yuhao
  • Su, Duo
  • Zhao, Xiaoxi

Abstract

This study distinguishes PFPs (Picture For Proof) from other NFT categories, as PFPs are primarily driven by aesthetics and community engagement. This work uses the Backward Sup Augmented Dickey–Fuller (BSADF) test to detect bubbles in the time-series market capitalization data. 13 projects are selected. We utilize t-distributed stochastic neighbor embedding(T-SNE) visualization for style similarity analysis. We also leverage Visual Geometry Group (VGG)-19 as the feature extractor for image similarity within the collections. Our results indicate that PFP collections with intellectual property (IP) rights and low image similarity exhibit the largest financial gain in the long term.

Suggested Citation

  • Tian, Yingjie & Xie, Yuhao & Su, Duo & Zhao, Xiaoxi, 2023. "Picture For Proof(PFPs): Aesthetics, IP and post launch performance," Finance Research Letters, Elsevier, vol. 55(PB).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pb:s154461232300346x
    DOI: 10.1016/j.frl.2023.103974
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    References listed on IDEAS

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    5. Yao, Can-Zhong & Li, Hong-Yu, 2021. "A study on the bursting point of Bitcoin based on the BSADF and LPPLS methods," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    6. Maouchi, Youcef & Charfeddine, Lanouar & El Montasser, Ghassen, 2022. "Understanding digital bubbles amidst the COVID-19 pandemic: Evidence from DeFi and NFTs," Finance Research Letters, Elsevier, vol. 47(PA).
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