Blockchain Games: What On and Off-chain factors affect the volatility, returns, and liquidity of Gaming Crypto Tokens

Blockchain games took the internet by storm as they offered a new way for users to play video games, own the assets in those games, and benefit monetarily from their efforts. Through Non-Fungible Tokens (NFTs) and cryptocurrencies, new, Web3 games ushered in a unique asset class for retail and institutional investors to diversify into and benefit from. This paper uses cross-sectional data from 30 blockchain gaming companies to identify on and off-chain factors that affect the company’s token volatility, returns, and liquidity. A multiple linear regression found the percentage of tokens dedicated to a company’s private sale and rewarding users, the length of a token’s vesting period, if the token has a fixed supply, and tokens based on the Solana or Polygon blockchains positively affect the volatility of that token. Conversely, the Monthly Active Users of the game, the token’s market capitalization, the amount of funds raised by the company, and the game genre negatively affect volatility. Funds raised, game genre, and Solana-based tokens were also significant in the returns model. Lastly, the number of faucets for the game and the percentage of tokens dedicated to rewards and the private sale showed significance in the liquidity model. This paper adds to the literature in the NFT, cryptocurrency, and blockchain gaming spaces

Financial Innovation and Technology after COVID-19: a few Directions for Policy Makers and Regulators in the View of Old and New Disruptors

Innovation and technology have led to the redefinition of business models and development of new ones in many bricks and mortar sectors.  Similarly, blockchain and fintech have impacted the finance and banking industries and are expected to further affect them in the future, leading some media to coin the expression “Uberization of banking”.  The authors extrapolate from sharing economy models to conclude that while blockchain and fintech are poised to advance finance and banking, there are no disruptive features that corroborate the term.  By analogy and successive approximations, this article identifies the limitations of the arguments for disruption in finance and banking.  Besides, hinging upon stylized facts, the article establishes similarities with sharing economy models to identify potential threats stemming from financial innovations such as Tokenomics, tagged as “no-ABSs”.  Eventually, the authors identify entry points and ways forward arising from the COVID-19 pandemic for policy makers and regulators to regain their pivotal role in policing the market and ensuring transparency while driving innovation

Valuation of Loyalty Tokens

Valuation of tokens is a wager on the platform adoption. This study investigates the effect of platform adoption on the valuation of loyalty tokens and the contingent claims with the token as an underlying. The platform adoption is modelled using the classical Bass Model. The example selected is that of airmiles, but the approach could be extended to loyalty token with other numeraires as well. After assuming few monetary policy rules for the platform governance, the proposed simple model predicts that the Bass Model parameters could have significant influence on the valuation of loyalty tokens and the contingent claims with the token as an underlying

Trend-­following strategies for cryptocurrencies with machine learning

Cryptocurrencies could bring big returns, but they also carry high volatility and big crash sizes. I discovered that trend­following strategies help investors to mitigate cryptocurrency’s risk. I also tested and confirmed that risk managed momentum strategy is applicable to the cryptocurr ency environment and that machine learning implementation further improves volatility reduction.Cryptomoedas poderão levar a retornos elevados, contudo também podem estar expostos a maior volatilidade e quedas excessivas do mercado. Eu descobri que estratégias que seguem tendências ajudam investidores a reduzir o risco das cryptomoedas. Também testei e confirmei que estratégias que gerem o risco de momentum podem ser aplicadas a cryptomoedas e que machine learning contribui para reduzir a exposição a volatilidade

Travels along the hype cycle: a set of blockchain applications and the economic processes they impact

Some commentators refer to blockchain as a potential General Purpose Technology. Yet despite a plethora of cryptoassets and projects, it has struggled to gain traction beyond payments and price discovery. This thesis explores how the technology is being applied to better understand the potential and risks of deploying blockchain. It examines four different use cases with econometric and case study methods: (1) Bitcoin mining as the token incentivized processing of records, (2) Initial Coin Offering tokens as a form of venture financing, (3) Uniswap the decentralized exchange and (4) Kompany improving the data integrity of compliance records via notarization to a public blockchain. It finds that blockchain enables capabilities that did not exist before, but that these capabilities are bounded by trade offs and developer priorities. Ultimately this research expands the literature on blockchain applications and argues that blockchain does not build better systems, but different systems that can achieve different objectives. It provides evidence that firms and society are gradually traversing the hype cycle, deploying blockchain, solving real world economic problems and creating value

Crypto-environment network connectivity and Bitcoin returns distribution tail behaviour

This study explores whether and to what extent cryptocurrency ecosystem network connectivity predicts Bitcoin returns across quantiles of the return distribution. The facets of cryptocurrency ecosystem network connectivity we consider include connectivity between the on- and off-chain segments of the Bitcoin market, the intensity and synchronization of social and traditional crypto-focused media activity, the intensity of network correlations between cryptocurrencies. We identify tail behaviour predictors employing a quantile regression approach. The results demonstrate the effectiveness of several connectivity measures in predicting both price spikes and downfalls, but in a different way before and during the COVID-19 outbreak

Statistical Modeling and Analysis

Die Blockchain-Technologie revolutioniert die Interaktion zwischen Menschen durch Peer-to-Peer-Netzwerke, Kryptografie und Konsensalgorithmen. Trustless Trust ermöglicht sichere und transparente Transaktionen ohne Zwischenhändler. Trotz der zunehmenden Beliebtheit von Krypto-Assets und den damit verbundenen „Tokenomics“ hat die Öffentlichkeit immer noch kein umfangreiches Wissen über die Funktionsweisen dieser Technologie, und ein Großteil des Diskurses bleibt spekulativ. Das Hauptziel dieser Arbeit ist, die grundlegenden Prinzipien von Krytowährungen (Cryptos) und Non-Fungible Tokens (NFTs) zu untersuchen sowie eine Korrelation zwischen der Technologie und ihren Auswirkungen auf die Wirtschaft aus statistischer und wirtschaftlicher Sicht herzustellen. Um dieses Ziel zu erreichen, wird in den Kapiteln 2 und 3 der Einfluss der Blockchain-Technologie auf Ökonomie und Funktionsweise von Kryptowährungen anhand ökonometrischer Modelle und Clustering-Techniken untersucht. Kapitel 3 untersucht Kryptowirschaft und Blockchain-Funktionalität anhand empirischer Methoden, insbesondere für Coincreatoren und Investoren. Wir zeigen am Beispiel von Ethereum, dass die wirtschaftliche Leistung von Kryptowährungen durch die Gestaltung der ihnen zugrunde liegenden Blockchain-Technologie beeinflusst werden kann. Kapitel 4 untersucht die partiellen Korrelationen von Bitcoin-Renditen über neun verschiedene Zentralbörsen aus der Perspektive eines hochfrequenten, dynamischen Netzwerks. Die vorgeschlagene MHAR-CM liefert Kovarianzschätzungen, die die Besonderheiten der Kryptomärkte berücksichtigen. Das Kapitel zeigt Spillover- und Third-Party-Risiken zwischen diesen Börsen. Kapitel 5 verwendet eine Hedonische Bewertungsmethode, um den DAI Digital Art Index basierend auf dem NFT-Kunstmarkt zu konstruieren. Ein besonderer Fokus liegt auf der Nivellierung der Auswirkungen von Ausreißern mit einer einstufigen robusten Regressions-Huberisierung und einem dynamic conditional score model. Diese Arbeit verknüpft neue Technologien und Wirtschaft durch statistische Modellierung und Analyse. Durch die Bereitstellung empirischer Belege beobachten wir, wie die Blockchain-Technologie unsere Wahrnehmung von Geld, Kunst und anderen Branchen verändert.The emergence of distributed ledger technologies, such as blockchain, has revolutionized how individuals interact by enabling "trust-less trust" through peer-to-peer networks, cryptography, and consensus algorithms. This technology eliminates intermediaries and provides secure, transparent transaction methods. However, public understanding of this technology, along with "Tokenomics", remains limited, resulting in speculative discourse. The main objective of this thesis is to investigate the fundamental principles of cryptocurrencies (cryptos) and non-fungible tokens (NFTs) and establish a correlation between the technology and its economic impact from statistical and economic perspectives. To achieve this, Chapters 2 and 3 explore the influence of blockchain technology on the economic and functional performance of cryptos using econometric models and clustering techniques. Chapter 3 presents an empirical framework that offers insights to coin creators and investors regarding the interplay between cryptonomics, blockchain functionality, and market dynamics. The economic performance of cryptocurrencies, illustrated with Ethereum as an example, is shown to be affected by the design of their underlying blockchain technology. Chapter 4 examines partial correlations of Bitcoin returns across nine centralized exchanges from a high-frequency dynamic network perspective. The proposed MHAR-CM provides reasonable covariance estimates that account for the unique characteristics of crypto markets. This chapter uncovers spillover risk and counterparty risk among these exchanges. In Chapter 5, a hedonic regression approach is employed to construct the DAI digital art index for the NFT art market. Special emphasis is given to mitigating the impact of outliers using one-step robust regression Huberization and a dynamic conditional score model. The DAI index enhances our understanding of this emerging art market and facilitates observation of its macroeconomic trends. This thesis establishes a connection between emerging technologies and the economy through statistical modeling and analysis. By providing empirical evidence, we gain insights into how blockchain technology is transforming our perceptions of money, art, and various industries

Behavioral Anomalies in Cryptocurrency Markets

If behavioral biases explain asset pricing anomalies, they should also materialize in cryptocurrency markets. I test more than 20 stock return anomalies based on daily cryptocurrency data, and document strong evidence of price momentum. Controlling for market and size, price momentum remains statistically significant, whereas price reversal and risk-based anomalies are weak. Cryptocurrency anomalies can be explained by behavioral theories that emphasize noise trader risks than fundamental risks