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A note on the determinants of NFTs returns

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  • Theodore Panagiotidis

    (University of Macedonia, Greece)

  • Georgios Papapanagiotou

    (University of Macedonia, Greece)

Abstract

We aim to identify the determinants of non-fungible tokens (NFTs) returns. The ten most popular NFTs based on their price, trading volume, and market capitalisation are examined. Twenty-three potential drivers of the returns of each NFT are considered. We employ a Bayesian LASSO model which takes into account stochastic volatility and leverage effect. The results indicate that NFTs returns are primarily driven by volatility and ethereum returns. We find a weak connection between NFTs returns and conventional assets, such as stock, oil, and gold markets.

Suggested Citation

  • Theodore Panagiotidis & Georgios Papapanagiotou, 2024. "A note on the determinants of NFTs returns," Working Paper series 24-07, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:24-07
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    More about this item

    Keywords

    Non-fungible tokens; cryptocurrency; LASSO; Bayesian; volatility;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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