Article Preview
TopIntroduction
Non-fungible tokens (NFTs) are tradeable rights to digital assets whose ownership is recorded in smart contracts. In other words, they configure a new form of ownership that gives value to assets in a digital form. These digital assets - images, videos, characters, music, game record, text, virtual creations, among others - can be traded using digital cryptocurrency payments registered on the blockchain (e.g. Ethereum and Flow blockchains) (Bao & Roubaud, 2022; Dowling, 2022a, 2022b). The value of NFTs are hard to ascertain as they do not usually provide future cash flows, and are more akin to art than to stocks. Well known NFT projects that have skyrocketed in prices include Crypto Punks and Bored Apes whose prices have exceeded 100k USD per a single image in 2022.1 Beeple’s “Everydays: the First 5000 Days” sold for around $69 million, making it among the most expensive NFT ever minted.
Unlike crypto coins and tokens that are fungible, NFTs are cryptographic assets that are non-fungibile. This means that each NFT item is a uniquely identified code with its own distinguishable metadata. Cryptocurrencies are interchangeable, and one digital coin is indistinguishable from another coin of the same ecosystem. The key characteristic of NFTs is the uniqueness of each token. Restricted ownership is granted by offering a unique digital certificate of ownership for the NFT, and their ownership records cannot be modified (Dowling, 2022b; Umar et al., 2022).
The trade volume of NFTs has increased in recent years, experiencing record sales especially after the Covid-19 pandemic. The effects of Covid-19 in the dynamics of financial markets, including cryptocurrencies movements, has started to be investigated (Conlon et al., 2020; Conlon & McGee, 2020; Goodell & Goutte, 2021a, 2021b). Mobility restrictions enhanced digital engagement and, consequently, the interest in cryptocurrencies and digital assets. In 2020, sales volume of NFTs was approximately 95 million US dollars. By the end of the second quarter of 2021, the NFTs trade reached 2.5 billion US dollars (Aharon & Demir, 2022).
The increase interest in NFTs started to be reflected in academia in the last few years. However, the topic is still under-researched in the fields of business, economics and finance despite its growing relevance. NFTs are considered one of the best recent economic innovations, creating new ways to tie technology and economic value and breaking down financial borders. NFTs democratized the access to digital assets and captured the interest of venture capitalists, Big Tech, digital and social media platforms (Laurence, 2021; Williams, 2022). Nevertheless, little is known about their pricing dynamic and relevant factors affecting it, especially network determinants impacts on prices.
Moreover, while previous studies aiming to investigate pricing determinants of NFTs made significant contributions (e.g., Horky et al., 2022; Kräussl & Tugnetti, 2022; Nadini et al., 2021), they mostly worked with partial datasets, metrics, and linear models. We aim to broaden the understanding of the NFTs pricing determinants by applying automated machine learning (AML). We used comprehensive data from Signex.io, a platform that helps investors to find NFT projects using general and social metrics from Twitter, Discord, Reddit and others.
We contribute to the field in two ways. First, we seek to provide further understanding on NFTs pricing determinants with special attention to network aspects. Big Tech and online communities and platforms act as connectors, influencing the evolution of the NFTs market. We develop a comprehensive model for NFTs pricing that includes network metrics, verifying that Big Tech are relevant and important predictors of NFT prices (Bao & Roubaud, 2022; Nobanee & Ellili, 2022).