Do online narratives leave a measurable imprint on prices in markets for digital or cultural goods? This paper evaluates how community attention and sentiment relate to valuation in major Ethereum NFT collections after accounting for time effects, market-wide conditions, and persistent visual heterogeneity. Transaction data for large generative collections are merged with Reddit-based discourse measures available for 25 collections, covering 87{,}696 secondary-market sales from January 2021 through March 2025. Visual differences are absorbed by a transparent, within-collection standardized index built from explicit image traits and aggregated via PCA. Discourse is summarized at the collection-by-bin level using discussion intensity and lexicon-based tone measures, with smoothing to reduce noise when text volume is sparse. A mixed-effects specification with a Mundlak within--between decomposition separates persistent cross-collection differences from within-collection fluctuations. Valuations align most strongly with sustained collection-level attention and sentiment environments; within collections, short-horizon negativity is consistently associated with higher prices, and attention is most informative when measured as cumulative engagement over multiple prior windows.
Open access
3 source records
econ.GN
Consumer Behavior in Brand Consumption and Identification
Distributed by Grasshopper Film, 12 East 32nd St., 4th Floor, New York, NY 10016Produced by Nicholas Bruckman, Shawn Hazelett, and Rahilla ZafarDirected by Nicholas Bruckman2024, Streaming, 77 mins Minted: The Rise (And Fall?) of the NFT, directed by Nicholas Bruckman, focuses on the explosive growth of the NFT (non-fungible token) digital art market in the late 2010s and early 2020s. Bruckman introduces how NFTs are situated within broader conversations about creativity, ownership, and value in digital environments. Using interviews with artists, collectors, technologists, and cultural critics, the viewer is asked to consider how NFTs are not simply a speculative trend, but rather a disruption, a way to represent artwork as a token for transactions that bypass traditional intermediaries in the art world (like galleries and museums). The strength of the film is Bruckman’s highlighting of the experiences of artists with new opportunities for visibility and economic independence through their NFTs. Notably, the documentary amplifies the perspectives of some female and BIPOC creators, framing NFTs as a space that seems to offer alternatives to the exclusionary and gatekeeping structures of the traditional art market. While the film highlights these voices, it stops short of fully examining whether the NFT ecosystem dismantled or merely reproduced the existing inequities within the art world. Minted is a timely film for conversations about digital literacy, information ethics, and the economics of creative labor. While the documentary does not offer a comprehensive critique of blockchain systems, it is successful as a snapshot of a significant cultural moment and a useful prompt for viewers to question the intersections of art, technology, and society. Awards:SXSW, Audience Award; Next Generation Indie Film Awards, Best Documentary Feature; Cordillera International Film Festival, Grand Jury Award for Best Documentary
Min-Bin Lin, Bingling Wang, Fabian Y R P Bocart, Christian M Hafner · 5 authors
Abstract The market of non-fungible tokens (NFTs), driven by blockchain and smart contracts, provides both artists and art collectors an unprecedented marketplace with more security, flexibility, publicity, and freedom to monetize. Yet, the emergence of such a market has been considered to be packed with speculation and economic uncertainty, given the limited understanding towards this market. To provide a precise depiction of the NFT art market and gauge market volatility, we construct the Digital Art Index, a novel price index using hedonic regression on the top 10 liquid NFT art collections (as of 2023). Addressing artwork price inequality, which often disrupts the price discovery process, this paper introduces two innovative alternative methods: Huberization and score-based filtering. These methods effectively mitigate the influence of outliers, particularly in an emerging market with limited accessible observations. In conclusion, the NFT art market presents significant opportunities for large gains, which are often favoured by risk-takers, but also carries the potential for significant losses. Its pricing is necessarily determined by institutional creators and platforms, meaning that solo artists may not benefit significantly in the current market environment.
Non-fungible tokens (NFTs) are widely used to distribute and authenticate digital artworks, yet minting practices across Ethereum, Solana, and Tezos sometimes diverge from core blockchain objectives, decentralization, immutability, and verifiable on-chain identity, thereby limiting their suitability as long-term certificates of authenticity. This study examines the technical, structural, and archival sources of these limitations and introduces a framework grounded in immutability, extended metadata and cryptographic signatures. Within this framework, the extended metadata file serves as the primary source of authenticity by self-sufficiently integrating the artist’s identity, artwork identification, edition semantics, token identification, and preservation guidance. The paper further evaluates decentralized storage models relevant to certification-grade use cases. It compares private servers, fully on-chain metadata, Arweave, and IPFS in terms of verifiability, sustainability, and long-horizon stewardship burden. Although Ethereum's ERC-721 serves as a reference implementation to anchor terminology and verification procedures, the proposed requirements are ecosystem-independent as long as the ecosystem meets the principles of decentralization, immutability and adoption. By aligning NFT issuance with established digital-preservation frameworks (OAIS, InterPARES, LOCKSS, PREMIS), this work offers a concrete foundation for future ERC/EIP proposals, preservation policy, and interdisciplinary research on durable, independently verifiable digital-art authenticity.
In the decade since the first edition of this volume, there has been an upheaval in the digital art world that saw the rise and fall of NFT (non-fungible token) art sales, some astronomical auction prices for digital art and NFTs, the creation of artist resale rights, and a rapid transformation in musical, material, and performance art distribution, thanks to the streaming economy, the subscription economy, and the sharing economy. Furthermore, generative AI can now turn users’ voice commands into works of art.
We assess the cross-sectional relation between media coverage and cryptocurrency returns using 7.6 million news articles from a large-scale web corpus. We find that cryptocurrencies with no coverage earn higher risk-adjusted returns than those with high coverage. By decomposing coverage intensity into coverage breadth and novelty, we separate the dissemination of existing information from the arrival of new information. We show that media coverage combines two offsetting channels: breadth captures an attention-driven channel that predicts lower future returns, while novelty captures an information channel that predicts higher future returns. Our findings highlight the role of information diffusion in cryptocurrency returns.
This paper examines the relationship between hype-driven sentiment and Bitcoin price movements using a data-driven approach. Public interest is proxied through Google Trends data, while market performance is measured using historical Bitcoin returns. The study finds no significant contemporaneous relationship between sentiment and returns. However, a weak negative relationship is observed between current sentiment and future returns, suggesting that periods of heightened public attention may precede market corrections. These findings indicate that hype does not drive immediate price movements but may act as a contrarian indicator of short-term market dynamics.
This study revisits calendar anomalies in cryptocurrency markets using hourly data for four actively traded cryptocurrencies (Bitcoin, Ethereum, Tether USDt, and BNB) and eight less active cryptocurrencies. While prior studies based on daily returns provide mixed evidence on day-of-the-week (DoW) effects, we show that these patterns are not persistent daily phenomena. Instead, they are driven by a limited number of intraday intervals and do not reflect broad daily behavior.We further document that these effects are localized, asset-specific, and more pronounced among actively traded cryptocurrencies, while largely absent among less active ones.Overall, the findings indicate that cryptocurrency markets exhibit limited and short-lived inefficiencies rather than persistent anomalies. This highlights the importance of employing high-frequency data in studies of continuously traded markets and suggests that digital asset investors may benefit from the presence of abnormal returns only in a limited number of hours on specific days of the week.
This paper documents a robust size-dependent pattern in cryptocurrency return predictability. Small coins exhibit strong short-term reversal, whereas large coins exhibit momentum, and the relation varies monotonically across the size distribution. We further show that these two sides of the pattern reflect different return dynamics: small-coin reversal is driven mainly by rebounds among recent losers, while large-coin momentum reflects their continued underperformance. Liquidity frictions and idiosyncratic volatility explain part of this pattern, but not all of it. These findings point to a "size-momentum puzzle" in cryptocurrencies.
The main objective of this paper is to outline the psychological aspects of trading in the music NFT (non-fungible tokens) ecosystem, with special emphasis on the psychological background of buying NFTs. Since the most important feature of NFTs is the acquisition of ownership enabled by technological solutions, we assume that each purchase of a token does not only imply an economic exchange of ownership, but also the activation of psychological ownership. Having in mind that psychological ownership is a relative category that depends, among other factors, on the nature of the target to which it is attached, our investigation is conceptual rather than empirical. By connecting the already identified cores of psychological ownership to the characteristics of some of the most prominent music NFT drops, we aim to theoretically define general dimensions of psychological ownership through which emotional and social connections to music NFTs as objects of ownership emerge. We conclude that the NFT market reinforces psychological ownership by providing consumers valuable outcomes. In terms of music NFTs, the concept of psychological ownership can be explained by several intertwined dimensions that create emotional and social connections and motivate users to purchase these digital goods. These include a sense of unique possession, identity and self-expression, a sense of belonging to a community, and investment opportunities. The NFT drops discussed illustrate how leveraging different aspects of psychological ownership can transform a music release into a special experience that reshapes the relationship between fans and musicians. Examining fans’ purchases of music NFTs from a psychological perspective can help musicians better understand blockchain users’ behaviour towards music, which is essential for developing NFTs into a sustainable digital format for music revenue.
Non-fungible tokens (NFTs) present luxury brands with a pricing dilemma: high prices sustain quality inferences but invite visible failure on transparent blockchain markets, whereas low prices stimulate demand but anchor perceptions downward. This research investigates zero pricing (free distribution) as a strategy to navigate this dilemma. Analysis of 65 NFT collections from 32 brands on OpenSea and 22,841 posts on X is followed by six experiments (N = 1,924). Low-priced NFTs inflict the most severe loss of brand luxuriousness, yet free NFTs attenuate this loss to levels indistinguishable from comparable pricing (Study 1). This attenuation does not extend to physical products, implicating congruence between inferred cost structure and zero pricing as a governing condition (Study 2). When secondary-market demand declines, free NFTs weaken failure inferences that otherwise erode perceived luxury; however, this buffer dissipates when the NFT features flagship brand elements (Studies 3a-3c). When demand increases, free and paid NFTs yield equivalent recovery (Study 4). Free distribution thus caps downside risk without forfeiting upside potential. These findings advance the zero-price literature by establishing inferred cost structure as a boundary condition for the anchor-shift mechanism and equip brand managers with a pricing approach calibrated to the transparency of blockchain-based markets.
Open access
Consumer Behavior in Brand Consumption and Identification
Non-fungible tokens (NFTs) are assets on a blockchain that represent ownership of digital art and are traded on NFT marketplaces. The NFT market on the Ethereum blockchain was monopolistic until the end of 2022, when a new marketplace entered and captured a significant market share. This paper collects transactions from these marketplaces to study the effects of increased competition on the incumbent marketplace, artists, and investors. While competition had positive effects by reducing transaction costs, increasing trading volume and attracting new users, it decreased the profits of artists, discouraged them from creating new artwork, and thereby reduced the supply of new assets. I also study user migration, multi-homing behavior, and market segmentation, and compares the results with the predictions from theories of platform economics.
Non-fungible token (NFT) markets are thin and typically settle in a cryptocurrency, so stress in the settlement asset can translate into abrupt drawdowns. This letter asks whether observable Ethereum (ETH) risk states provide an ex-ante ranking of crash risk in a curated art-NFT marketplace. Using SuperRare sales aggregated to a daily price proxy (2021–2023), we sort days by (i) 7-day realized ETH volatility and (ii) the filtered high-volatility probability from a two-state Markov-switching model. Forward 30-day drawdown crashes are sharply monotone across state quartiles: for example, a 30% USD crash rate rises from 9.9% to 38.8% from the lowest to highest volatility-probability quartile. Because crash windows overlap mechanically, conventional logit inference is overconfident; we therefore report main results as conservative linear probability models with Newey–West HAC errors and a moving-block bootstrap (logit results appear in the appendix for comparison). We further confirm results using a fully real-time state proxy based on an expanding-window volatility threshold, and document that crash predictability is strongest during the 2022 market stress episode, consistent with ETH risk regimes activating precisely when tail risks materialise. The settlement asset operates as a tail-risk switch for art NFTs, with limited corresponding mean-return predictability.
Despite trading volumes in the tens of billions, NFT markets are illiquid: median quoted spreads of 48-200% far exceed equity levels, though execution-based measures covering nearly all sales yield effective costs of only 2-5%. Using over 410 million orderbook events-including, for the first time, comprehensive bid-side data-across six major collections, we document a distinctive institutional response: a two-tier orderbook in which collection-level floor bids, rather than token-specific orders, supply the dominant source of buy-side liquidity. A small number of algorithmic market makers provide these bids but face adverse selection inherent in collection-level offers, experiencing market-adjusted post-purchase returns of-3% to-7%. In panel regressions, collection identity absorbs over 30 percentage points of R-squared , dominating all observable spread determinants. A comparison of the same 10 000 assets under two market structures reveals that the native bilateral marketplace achieves tighter spreads (54% vs. 200%), suggesting that ease of bidding generates liquidity activity but not price efficiency.
Rarity is a key determinant of value in non-fungible token markets, yet its measurement remains fragmented, opaque, and theoretically underdeveloped. We analyse the statistical and combinatorial rarity metrics used by major platforms and show that most reduce to transformations of the Pythagorean means. The widely-used OpenRarity metric produces rankings identical to the geometric mean of attribute frequencies and is therefore not a new methodology. However, this approach admits a coherent probabilistic interpretation only under the assumption of trait independence. Alternative arithmetic- and harmonic-mean metrics lack theoretical justification, while the Jaccard distance is structurally biased when metadata omit missing traits. When metadata are standardised appropriately, Jaccard-based rankings are identical to the arithmetic mean ranks. These findings explain pervasive inconsistencies in rarity rankings and help explain the weak empirical relationship between price and rarity. We propose a standardised, theoretically grounded framework for rarity measurement that accommodates dependence structures and corrects metadata bias.
NFTs provided an extraordinary real-time laboratory for bubble economics: returns were exceptionally right-skewed, illiquidity pervaded even the most active platforms, and a handful of trades drove aggregate performance. Investors extrapolating from realized returns without recognizing selection bias and survivorship faced a substantial risk of disappointment. As our data and simulations confirm, successful NFT investing during the bubble required an almost perfect confluence of timing, liquidity, and luck. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org .
AbstractThis article investigates the economic and behavioral feasibility of creating personalizedcryptocurrencies (Fan Coins) linked to the performance of soccer players, using quantitative methods inEconometrics, focusing on box office revenue, sponsorships and sports betting. The analysis includes theThe cases of Diego Ribas (Flamengo), Neymar (Santos), and top scorers from São Paulo and Palmeiras.proposal is to analyze how reputation and sports performance can be transformed into digital assets withmeasurable value. Furthermore, it is proposed to use artificial intelligence systems to manage sponsorportfolios and a fan club application with a subscription system to foster a new sports business model basedon data and personalization.Keywords: Fan Coin; Cryptocurrency; Econometrics; Sports Economics; Game Theory;Behavioral Finance; Sports Betting; Artificial Intelligence; Financial Modeling; Digital Sponsorship
This article examines the NFT market and art tokenization in the context of money laundering. It explores the evolution of the art market toward digitalization, the definition of NFTs, and their legal and technical aspects. Additionally, it highlights the rapid growth of the market and associated risks, such as fraud, sanction evasion, and money laundering. It discusses mechanisms for concealing illicit funds, as well as the lack of clear regulations and oversight of NFT platforms within the AML/CFT framework. It emphasizes the need for regulatory clarification, the establishment of transaction registries, and addresses other unresolved issues related to NFTs, including intellectual property protection and tax obligations.
Mazin Nawwaf Assi, Sumeet Kaur, Swati Chaudhary, Pompi Das Sengupta · 7 authors
With the fast adoption of artificial intelligence in the art and cultural industry, the production, curation, distribution, and management of creative works have been radically transformed. Intelligent systems that allow artists, curators, institutions, platforms, and intelligent systems to work together in continuous interaction are now known as AI-driven art ecosystems. The paper explores management innovation as it manifests in AI-based art systems, the changes in managerial practices, forms of governance and decision making, in reaction to advanced computational creativity and data-driven work. The paper conceptualizes AI-based art systems as multi-layered systems that include creative production, curatorial intelligence and digital distribution systems such as online galleries and non-fungible token-based markets. It emphasizes the ways in which management innovation is developed in the form of a workflow redesign that combines automation and human-AI partnership to allow efficiency without sacrificing artistic intent and cultural sensitivity. Additionally, the paper focuses on the governance innovations that respond to the issues of transparency, accountability, ethical compliance, and authorship attribution in creative settings with algorithms mediating them. The resource orchestration is considered a key managerial competency with a focus on the strategic alignment of data resources, innovative talent, and computing resources. The study further examines the AI-enhanced decision-making in the context of art institutions and how the predictive analytics and the intelligent recommendation systems can be used in audience engagement prediction, curatorial planning, and portfolio management. Based on the selected case studies of AI-integrated museums, hybrid creative studios, and global AI-art hubs, the paper finds the best practices and benchmarking perspectives.
Sandip Sane, Dr. Diksha Tripathi, Anagha Bhope, Aditee Huparikar Shah · 7 authors
One of the ways in which blockchain technology is transforming the visual arts ecosystem is by providing decentralized, transparent, and verifiable systems of ownership, distribution, and value exchange of digital art. This paper analyzes how blockchain has been disruptive to visual arts in modern times, specifically in non-fungible tokens (NFTs), creative economies, and artist-collector relationships. Historically, the digital artworks were associated with the issues with provenance, copyright protection, scarcity, and justifiable monetization. Blockchain overcomes these weaknesses by providing immutable registries, smart contracts, and tokenization to allow artists to have verifiable ownership, determine authenticity, and earn automatic royalties on transactions in the secondary market. The study takes a conceptual and analytical structure by synthesising the extant literature, platform case studies and new blockchain-based art markets to assess the worth of NFTs in redefining artistic value, authorship and market forces. The results suggest that blockchain makes global art markets more democratic by decreasing the use of intermediaries including galleries and auction houses, which are central, and thus giving power to independent and new artists. Simultaneously, it cultivates new creative economies in which digital scramble, community contribution and speculative finance overlap. Nevertheless, the paper also singles out some fundamental challenges such as environmental sustainability issues, market unpredictability, regulatory ambiguity and the issues of artistic legitimacy and cultural value. The article presents the argument that although blockchain does not substitute the traditional art institutions, it supports them by providing hybrid ecosystems through integrations of physical and digital practices. All in all, the study suggests blockchain as a revolutionary infrastructure to the visual arts, reinventing ownership, trust, and economic frameworks and proposing a sustainable, ethical, and inclusive future to enable the long-term development of digital art ecosystems.
Dec 23, 2025·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Tejas Kotha, Kushagra Bhatnagar, Leona Chandra Kruse, Matti Rossi
NFTs (non-fungible tokens) promised the interaction of artists/creators directly with their collectors without the need for any intermediaries, but the realisation was quick that such a technology, instead of getting rid of intermediaries, reintroduced new intermediaries in the form of NFT marketplaces. These marketplaces exhibit diverse features and cater to different user groups. A wide array of governance strategies, such as curation and gatekeeping, are used to steer creativity and interactions in the marketplace, informed by the marketplace's strategy. We examined this diversity by identifying the 'ideal types' of marketplaces based on these strategies alongside the motivations of the creators to make sense of the growing NFT market and constructed a typology that distinguishes four kinds of NFT marketplaces: Avant-garde, Canonical, Mass Culture, and Coterie. The article also offers practical implications for creators and collectors looking to make informed choices when deciding to participate in a particular marketplace.
Wash trading is a major issue in non-fungible token (NFT) markets that distorts transaction volumes and returns. In this work, we examined the effect of wash trading by focusing on two specific NFT collections. First, we implemented a multi-layered wash trading detection algorithm to identify wash trades. Using regression analysis, we then showed that weekly transaction volumes of a heavily wash-traded collection can be magnified by two orders of magnitude compared to a cleaner collection. Moreover, wash trading resulted in positive returns in a collection that has extensive wash trading; in contrast, wash trading in the cleaner collection was penalized with negative returns, suggesting heterogeneity in both incidence and profitability of wash trading. Our findings provide a better understanding on the impact of wash trading on NFT markets and highlight the need to improve security in NFT markets and other decentralized financial technology systems. In particular, by extending transaction-level detection to collection characteristics, we could assess the impact of wash trading. This approach is easily replicable and enables market stakeholder to identify inauthentic activity and policy makers to provide adequate safeguards for these products.