Digital assets and the traditional financial sectors are increasingly interacting. In the field of cryptocurrency, the combination with the sports industry has received attention from fans and clubs, media, and academic circles. Based on the LASSO-VAR model which is suitable for large samples, this article investigates the connectivity between sports cryptocurrency Chiliz (CHZ) and listed European football club stocks. The results show that there is a certain interrelatedness among the selected assets, and it becomes closer with the outbreak of major emergencies. In addition, CHZ is a net recipient of spillovers, while club stocks show diversification. Our results are helpful for club fans, individual and institutional investors, market regulators, and policymakers to make correct decisions.
Automated Market Makers (AMMs) are a cornerstone of decentralized finance. They are smart contracts (stateful programs) running on blockchains. They enable virtual token exchange: traders swap tokens with the AMM for a fee, while liquidity providers supply liquidity and receive these fees. Demand for AMMs is growing rapidly, but our experiment-based estimates show that current architectures cannot meet the projected demand by 2029. This is because the execution of existing AMMs is non-parallelizable. We present SAMM, an AMM comprising multiple shards. All shards are AMMs running on the same chain, but their independence enables parallel execution. The security of SAMM, unlike in classical sharding solutions, relies on incentive compatibility. Therefore, SAMM introduces a novel fee design. Through analysis of Subgame-Perfect Nash Equilibria (SPNE), we show that SAMM incentivizes the desired behavior: liquidity providers balance liquidity among all shards, overcoming destabilization attacks, and trades are evenly distributed. We validate our game-theoretic analysis with a simulation using real-world data. We evaluate SAMM by implementing and deploying it on local testnets of the Sui and Solana blockchains. To our knowledge, this is the first quantification of high-demand-contract performance. SAMM improves throughput by 5x and 16x, respectively, potentially more with better parallelization of the underlying blockchains. It is directly deployable, mitigating the upcoming scaling bottleneck.
Lennart Ante, Aman Saggu, Benjamin Schellinger, Friedrich-Philipp Wazinski
This paper investigates the potential of blockchain-based fan tokens, a class of crypto asset that grants holders access to voting on club decisions and other perks, as a mechanism for stimulating democratized decision-making and fan engagement in the sports and esports sectors. By utilizing an extensive dataset of 3,576 fan token polls, we reveal that fan tokens engage an average of 4,003 participants per poll, representing around 50% of token holders, underscoring their relative effectiveness in boosting fan engagement. The analyses identify significant determinants of fan token poll participation, including levels of voter (dis-)agreement, poll type, sports sectors, demographics, and club-level factors. This study provides valuable stakeholder insights into the current state of adoption and voting trends for fan token polls. It also suggests strategies for increasing fan engagement, thereby optimizing the utility of fan tokens in sports. Moreover, we highlight the broader applicability of fan token principles to any community, brand, or organization focused on customer engagement, suggesting a wider potential for this digital innovation.
Mathew Fukuzawa, Brandon M. McConnell, Michael G. Kay, Kristin Thoney-Barletta · 5 authors
Purpose Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts. Design/methodology/approach Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results. Findings The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally. Research limitations/implications Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience. Practical implications Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost. Social implications Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams. Originality/value This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.
Decentralized exchanges are becoming a competitive necessity for Web3 users. However, they cannot beat centralized exchanges in terms of user experience. Due to expensive gas fees, the blockchain cannot implement the classic order book model which is the pillar for traditional finance exchanges. Instead, most decentralized exchanges operate on the Automated Market Maker (AMM) model using a pre-defined mathematical pricing rule. AMM is more efficient to run on the blockchain but the biggest tradeoff is impermanent loss for liquidity providers and price slippage for traders. This remains the most noticeable drawback of today’s AMM. In this paper, we make the following contributions. First, we observe that if AMM is virtualized as an order book, its “order-book" shape is awkwardly different from that of a real-world order book. We argue that this is conceptually connected to the above weakness. We are thus motivated to design an AMM, the first of its kind, that mimics the price impact behaviors of real-world order books. Second, the proposed AMM, thanks to this property, significantly outperforms the state-of-the-art AMM in impermanent loss. Interestingly, our AMM can even result in impermanent gain. We are also better for large orders where price slippage is a concern. Third, another feature is that, while today’s AMM typically requires a fixed inventory ratio for the liquidity pool, the new AMM allows this ratio to vary, giving liquidity providers flexible options for joining or exiting the pool. All these advantages are offered without losing desirable properties of an AMM regarding split-order exploitation, arbitrage risks, and liquidity continuity. Our findings are validated by theoretical analysis with mathematical proofs and, also, experimental evaluation which was comprehensively conducted using two real-world datasets and a synthetic dataset representing different market scenarios. Our research is the first in the literature on AMM design that factors in statistical properties from the order book model.
Krzysztof Gogol, Robin Fritsch, Malte Schlosser, Johnnatan Messias · 6 authors
This paper studies liquid staking tokens (LSTs) on automated market makers (AMMs), both theoretically and empirically. LSTs are tokenized representations of staked assets on proof-of-stake blockchains. First, we model LST-liquidity on AMMs theoretically, categorizing suitable AMM types for LST liquidity and deriving formulas for the necessary returns from trading fees to adequately compensate liquidity providers under the particular price trajectories of LSTs. For the latter, two relevant metrics are considered: (1) losses compared to holding the liquidity outside the AMM (loss-versus-holding, or "impermanent loss"), and (2) the relative profitability compared to fully staking the capital (loss-versus-staking) which is specifically tailored to the case of LST-liquidity. Next, we empirically measure these metrics for Ethereum LSTs across the most relevant AMM pools. We find that, while trading fees often compensate for impermanent loss, fully staking is more profitable for many pools, raising questions about the sustainability of the current LST liquidity allocation to AMMs.
The Indian sports industry is undergoing a substantial transformation in fan engagement, driven by evolving trends and technological innovations. This study comprehensively analyses the current state, methodologies, and implications of fan engagement within the Indian sports sector. In response to the COVID-19 pandemic, there has been a noticeable shift in traditional fan behaviour, with a decline in physical gatherings and a surge in alternative forms of participation such as co-watching, online discussions, sports betting, and content sharing. The research employs a multifaceted methodology, combining data collection, surveys, and trend analysis. It explores the Impact of cutting-edge technologies like Over-the-Top (OTT) media services, Non-Fungible Tokens (NFTs), blockchain technology, Artificial Intelligence (AI), and Virtual Reality (VR) on reshaping fan engagement. The dynamic and tech-driven nature of the Indian sports industry necessitates a holistic understanding of contemporary fan engagement strategies. This study aims to analyze the current landscape of fan engagement in Indian sports, explore methodologies employed, and assess the Impact of technological innovations on fan behaviour. Quantitative methods like data collection through surveys have been employed to gain insights into emerging trends and their influence on fan engagement. Survey data reveals the enduring dominance of cricket (46%) and the growing prominence of football (29%) among Indian sports fans. Notably, there is significant trust (46%) in in-game analysis technologies, indicating fans' readiness to embrace technological enhancements. While live stadium experiences remain popular, the survey underscores the role of digital platforms, with 57% preferring Hotstar for sports content. The rising popularity of fantasy league apps and the recognition of social media's Impact on player performance (64%) present opportunities for digital engagement. The study concludes by offering recommendations for businesses and stakeholders to adapt to the changing landscape. It underscores the importance of integrating innovative technologies, fostering online fan communities, and tailoring content and experiences to cater to the evolving expectations of Indian sports enthusiasts.
Gambling sponsorships are common in international soccer due to the substantial funds they provide to clubs. For example, in the 2022/23 English Premier League season, eight clubs collectively received an estimated £60 million from gambling shirt-front sponsorships.While the Premier League plans to ban gambling shirt-front sponsorships by 2026, this will not include shirt sleeves or pitch-side hoardings, which are the most frequently seen forms of in-game marketing. In contrast, Italy and Spain have fully banned gambling sponsorships and in-game marketing due to public health concerns. Relatedly, much less attention has been paid to the emergence of sponsorships associated with cryptocurrency or financial trading. These are both gambling-like products, which are engaged in disproportionately by those experiencing gambling-related harm, and which also use soccer to market themselves. Researchers have suggested that these products might look to fill the gap in high- level sports left by gambling sponsorship bans, and so have highlighted the need to monitor their use of sponsorship agreements with high-level soccer teams. We therefore provide an overview of gambling and gambling-like sponsorship of soccer teams within high-level leagues across England, France, Germany, Spain, Italy, Portugal, and Argentina. Overall, our findings indicate that gambling sponsorship remains prominent, but has reduced in comparison to previous seasons across most countries. However, we have observed betting ‘partnerships’ which circumvent gambling sponsorship prohibitions in Italy. In relation to cryptocurrency and financial trading companies, there are limited numbers of active sponsorships outside of the UK, but ‘partnerships’ between teams and these companies have become prevalent.
Jamie Torrance, Conor Heath, Maira Andrade, Philip Newall
Background & aims: The gamblification of UK football has resulted in a proliferation of in-game marketing associated with gambling and gambling-like products such as cryptocurrencies and financial trading apps. The English Premier League (EPL) has in response banned gambling logos on shirt-fronts from 2026 onward. This ban does not affect other types of marketing for gambling (e.g., sleeves and pitch-side hoardings), nor gambling-like products. This study therefore aimed to assess the ban's implied overall reduction of different types of marketing exposure. Methods: We performed a frequency analysis of logos associated with gambling, cryptocurrency, and financial trading across 10 broadcasts from the 2022/23 EPL season. For each relevant logo, we coded: the marketed product, associated brand, number of individual logos, logo location, logo duration, and whether harm-reduction content was present. Results: There were 20,941 relevant logos across the 10 broadcasts, of which 13,427 (64.1%) were for gambling only, 2,236 (10.7%) were for both gambling and cryptocurrency, 2,014 (9.6%) were for cryptocurrency only, 2,068 (9.9%) were for both cryptocurrency and financial trading, and 1,196 (5.7%) were for financial trading only. There were 1,075 shirt-front gambling-associated logos, representing 6.9% of all gambling-associated logos, and 5.1% of all logos combined. Pitch-side hoardings were the most frequent marketing location (52.3%), and 3.4% of logos contained harm-reduction content. Discussion & Conclusions: Brand logos associated with gambling, cryptocurrency, and financial trading are common within EPL broadcasts. Approximately 1 in 20 gambling and gambling-like logos are subject to the EPL's voluntary ban on shirt-front gambling sponsorship.
Purpose This paper provides a thorough examination of Socios.com, a blockchain platform that integrates token sales with the fan experience in the sports industry. The study focuses on three key aspects: the performance, bubble phenomenon and dynamics of fan tokens. The author aims to address important questions that may concern potential supporters and investors. Might sports fans incur financial losses due to their team loyalty? Is the fan token market just a passing trend? Are fan tokens driven by the behaviour of the cryptocurrency market? Design/methodology/approach This analysis aims to involve several methodologies. The author evaluates the short- and long-term performance of fan tokens by computing first-day and buy-and-hold (abnormal) returns. The author also employs the Phillips, Shi, and Yu's (PSY) real-time bubble detection method to investigate the presence of bubble phenomenon in the fan token market segment. Finally, the author examines the potential dependences between fan tokens, Chiliz and the cryptocurrency market (represented by the CCi30 index) using both Pearson/Kendall correlations and the wavelet coherence approach. Findings The study presents three notable contributions to the existing literature. First, the author demonstrates that investing in fan tokens to support one's favourite sports teams can lead to financial losses, whereas traders can potentially outperform the market by investing in Chiliz. Second, the author states that fan tokens were a short-lived trend, as evidenced by their decline in value after the bubble burst in 2021. Third, the findings indicate that the fan token market was influenced by the cryptocurrency market and Chiliz during periods of market downturns. Originality/value To the best of author’s knowledge, this is the first paper to conduct a comprehensive analysis of the performance, bubble phenomenon and dynamics of the token market fan segment, along with the exclusive on-platform currency, Chiliz.
Abstract This statement presents the author’s proposition—“Let’s be more conceptual!”—in response to the attempt to interpret Non-Fungible Tokens (NFTs) as contemporary art. In the context of NFTs, this opinion has the significance of finding artistry in the underlying decentralized autonomous consensus-building, and in the context of contemporary art, it has the significance of leading to the revival of early conceptual art. The second half of this statement covers the novelty and feasibility of this opinion, referring to precedents in art and engineering.
Bambang Leo Handoko, Agustinus Winoto, Faris Kasenda, Citra Amanda · 5 authors
Investing in cryptocurrencies is one of the instruments that is increasingly in demand by individual investors today. Investors are starting to aim for other advantages of investing in cryptocurrencies besides capital gains, which is the benefits of getting airdrops. Through this research, we want to examine what factors influence investors' intention to invest through the cryptocurrency airdrops program. We take these factors from the behavioral finance approach. We use heuristic behavior, prospect theory and role of personality variables. Our research is a causal quantitative research. We collected primary data from a questionnaire distributed to experienced individual investors participating in one of the cryptocurrency airdrops programs. We use hypothesis testing with ordinary least square analysis. The research result is that heuristic behavior, prospect theory, and role of personality each has significant influence on investor decision making in cryptocurrency airdrops.
Mohak Goyal, Geoffrey Ramseyer, Ashish Goel, David Mazières
Constant Function Market Makers (CFMMs) are a tool for creating exchange markets, have been deployed effectively in prediction markets, and are now especially prominent in the Decentralized Finance ecosystem. We show that for any set of beliefs about future asset prices, an optimal CFMM trading function exists that maximizes the fraction of trades that a CFMM can settle. We formulate a convex program to compute this optimal trading function. This program, therefore, gives a tractable framework for market-makers to compile their belief function on the future prices of the underlying assets into the trading function of a maximally capital-efficient CFMM. Our convex optimization framework further extends to capture the tradeoffs between fee revenue, arbitrage loss, and opportunity costs of liquidity providers. Analyzing the program shows how the consideration of profit and loss leads to a qualitatively different optimal trading function. Our model additionally explains the diversity of CFMM designs that appear in practice. We show that careful analysis of our convex program enables inference of a market-maker's beliefs about future asset prices, and show that these beliefs mirror the folklore intuition for several widely used CFMMs. Developing the program requires a new notion of the liquidity of a CFMM, and the core technical challenge is in the analysis of the KKT conditions of an optimization over an infinite-dimensional Banach space.
Technology has begun to fundamentally change the sport industry. With the upsurge in the use of artificial intelligence, machine learning, virtual reality, and augmented reality, the sport industry has begun to use more technology to enhance the consumer experience. Along with the rise in these other technologies, is the use of blockchain technology. Blockchain technology is driven by three key pillars: (1) distributed computation, (2) public key cryptography, and (3) decentralized consensus. Blockchain is changing the sport landscape by supporting the use of non-fungible tokens for creative sport content, cryptocurrencies for purchases, and platforms that better protect consumer information and enhance their engagement opportunities with athletes, teams, and leagues. In this chapter, we discuss how blockchain technologies can provide opportunities and risks to the sport industry.
Christoph Schlegel, Mateusz Kwaśnicki, Akaki Mamageishvili
We study axiomatic foundations for different classes of constant-function automated market makers (CFMMs). We focus particularly on separability and on different invariance properties under scaling. Our main results are an axiomatic characterization of a natural generalization of constant product market makers (CPMMs), popular in decentralized finance, on the one hand, and a characterization of the Logarithmic Scoring Rule Market Makers (LMSR), popular in prediction markets, on the other hand. The first class is characterized by the combination of independence and scale invariance, whereas the second is characterized by the combination of independence and translation invariance. The two classes are therefore distinguished by a different invariance property that is motivated by different interpretations of the numéraire in the two applications. However, both are pinned down by the same separability property. Moreover, we characterize the CPMM as an extremal point within the class of scale invariant, independent, symmetric AMMs with non-concentrated liquidity provision. Our results add to a formal analysis of mechanisms that are currently used for decentralized exchanges and connect the most popular class of DeFi AMMs to the most popular class of prediction market AMMs.
Non-Fungible Token (NFT) markets are one of the fastest growing digital markets today, with the sales during the third quarter of 2021 exceeding $10 billions! Nevertheless, these emerging markets - similar to traditional emerging marketplaces - can be seen as a great opportunity for illegal activities (e.g., money laundering, sale of illegal goods etc.). In this study we focus on a specific marketplace, namely NBA TopShot, that facilitates the purchase and (peer-to-peer) trading of sports collectibles. Our objective is to build a framework that is able to label peer-to-peer transactions on the platform as anomalous or not. To achieve our objective we begin by building a model for the profit to be made by selling a specific collectible on the platform. We then use RFCDE - a random forest model for the conditional density of the dependent variable - to model the errors from the profit models. This step allows us to estimate the probability of a transaction being anomalous. We finally label as anomalous any transaction whose aforementioned probability is less than 1%. Given the absence of ground truth for evaluating the model in terms of its classification of transactions, we analyze the trade networks formed from these anomalous transactions and compare it with the full trade network of the platform. Our results indicate that these two networks are statistically different when it comes to network metrics such as, edge density, closure, node centrality and node degree distribution. This network analysis provides additional evidence that these transactions do not follow the same patterns that the rest of the trades on the platform follow. However, we would like to emphasize here that this does not mean that these transactions are also illegal. These transactions will need to be further audited from the appropriate entities to verify whether or not they are illicit.
We introduce the SPRIG (Smart Proofs via Recursive Information Gathering) protocol. SPRIG allows agents to propose, question, and defend mathematical proofs in a decentralized fashion. A structure of stakes and bounties aims at producing debates in good faith and if those persist, they must go down to machine-level details, where they can be settled automatically. This combination of economic incentives and an oracle is designed to promote succinct and informative proofs. SPRIG can run autonomously as a smart contract on a blockchain platform, and hence it does not rely on a central trusted institution. We translate SPRIG into a general game-theoretic model and prove that the protocol satisfies two desirable properties: no spamming and monotonicity. We then characterize analytically the equilibrium of a simple two-player specification of the model: this provides important insights into the impact of the protocol’s parameters on the probabilities that it induces type I/II errors. We conclude by discussing the main attacks SPRIG’s designers will need to take into account.
This article investigates the emerging segment of the cryptocurrency market related to football fan tokens (FFTs)—digital assets used for engagement with professional football clubs around the world. More specifically, the authors study the investability of FFTs from the perspective of risk and return. They find that FFTs generate a whopping 150% return on the first trading day. This return is significantly larger if the FFT market cap is higher, the FFT offer price is lower, the football team displays better historical performance, and the team is located in a relatively small metropolitan area with a high GDP per capita. They also find that in the long run, FFTs severely underperform all major crypto benchmarks, including NFT, DeFi, Meme, and bitcoin. Moreover, the returns to FFTs tend to be highly volatile (160% annualized). Intriguingly, they show that the real-life performance of football teams does not affect the contemporaneous market performance of their FFTs.