More Like this

1. The rise and fall of cryptocurrencies

   Feder, Amir; Gandal, Neil; Hamrick, JT; Moore, Tyler; Vasek, Marie (June 2018, Workshop on the Economics of Information Security)

   Since Bitcoin’s introduction in 2009, interest in cryptocurrencies has soared. One manifestation of this interest has been the explosion of newly created coins. This paper examines the dynamics of coin creation, competition and destruction in the cryptocurrency industry. In order to conduct the analysis, we develop a methodology to identify peaks in prices and trade volume, as well as when coins are abandoned and subsequently “resurrected”. We study trading activity associated with 1 082 coins over a nearly five-year period. We present evidence that the more frequently traded coins experience the biggest price rises. They are also much less likely to be abandoned, that is, to experience a drop in average trading volume to below 1% of a prior peak value. Overall, we find that 44% of publicly-traded coins are abandoned, at least temporarily. 71% of abandoned coins are later resurrected, leaving 18% of coins to fail permanently. We then examine the association between entry and exit and other key variables such as price, volume, and market capitalization in order to analyze and provide intuition underpinning the fundamentals in this market. We conclude by examining the bursting of the Bitcoin bubble in December 2017. Unlike the end of the 2013 bubble, some alternative cryptocurrencies continue to flourish after the fall of Bitcoin. 

   more » « less
2. Cryptocurrency Competition and Market Concentration in the Presence of Network Effects

   https://doi.org/https://doi.org/10.5195/ledger.2021.226  

   stylianou, kostantinos; spiegelberg, leonhard; herlihy, maurice; carter, nic (October 2021, Ledger)

   null (Ed.)

   When network products and services become more valuable as their userbase grows (network effects), this tendency can become a major determinant of how they compete with each other in the market and how the market is structured. Network effects are traditionally linked to high market concentration, early-mover advantages, and entry barriers, and in the market they have also been used as a valuation tool. The recent resurgence of Bitcoin has been partly attributed to network effects, too. We study the existence of network effects in six cryptocurrencies from their inception to obtain a high-level overview of the application of network effects in the cryptocurrency market. We show that, contrary to the usual implications of network effects, they do not serve to concentrate the cryptocurrency market, nor do they accord any one cryptocurrency a definitive competitive advantage, nor are they consistent enough to be reliable valuation tools. Therefore, while network effects do occur in cryptocurrency networks, they are not (yet) a defining feature of the cryptocurrency market as a whole. 

   more » « less
3. On the role of local blockchain network features in cryptocurrency price formation

   https://doi.org/10.1002/cjs.11547  

   Dey, Asim_K; Akcora, Cuneyt_G; Gel, Yulia_R; Kantarcioglu, Murat (March 2020, Canadian Journal of Statistics)

   <italic>Abstract</italic> Cryptocurrencies and the underpinning blockchain technology have gained unprecedented public attention recently. In contrast to fiat currencies, transactions of cryptocurrencies, such as Bitcoin and Litecoin, are permanently recorded on distributed ledgers to be seen by the public. As a result, public availability of all cryptocurrency transactions allows us to create a complex network of financial interactions that can be used to study not only the blockchain graph, but also the relationship between various blockchain network features and cryptocurrency risk investment. We introduce a novel concept of chainlets, or blockchain motifs, to utilize this information. Chainlets allow us to evaluate the role of local topological structure of the blockchain on the joint Bitcoin and Litecoin price formation and dynamics. We investigate the predictive Granger causality of chainlets and identify certain types of chainlets that exhibit the highest predictive influence on cryptocurrency price and investment risk. More generally, while statistical aspects of blockchain data analytics remain virtually unexplored, the paper aims to highlight various emerging theoretical, methodological and applied research challenges of blockchain data analysis that will be of interest to the broad statistical community.The Canadian Journal of Statistics48: 561–581; 2020 © 2020 Statistical Society of Canada 

   more » « less
4. A Panel Data Set of Cryptocurrency Development Activity on GitHub

   https://doi.org/10.1109/MSR.2019.00037  

   van Tonder, Rijnard; Trockman, Asher; Le Goues, Claire (May 2019, Proceedings of the 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR))

   Cryptocurrencies are a significant development in recent years, featuring in global news, the financial sector, and academic research. They also hold a significant presence in open source development, comprising some of the most popular repositories on GitHub. Their openly developed software artifacts thus present a unique and exclusive avenue to quantitatively observe human activity, effort, and software growth for cryptocurrencies. Our data set marks the first concentrated effort toward high-fidelity panel data of cryptocurrency development for a wide range of metrics. The data set is foremost a quantitative measure of developer activity for budding open source cryptocurrency development. We collect metrics like daily commits, contributors, lines of code changes, stars, forks, and subscribers. We also include financial data for each cryptocurrency: the daily price and market capitalization. The data set includes data for 236 cryptocurrencies for 380 days (roughly January 2018 to January 2019). We discuss particularly interesting research opportunities for this combination of data, and release new tooling to enable continuing data collection for future research opportunities as development and application of cryptocurrencies mature. 

   more » « less
5. MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense

   https://doi.org/10.1145/3243734.3243858  

   Konoth, Radhesh Krishnan; Vineti, Emanuele; Moonsamy, Veelasha; Lindorfer, Martina; Kruegel, Christopher; Bos, Herbert; Vigna, Giovanni (October 2018, 2018 ACM SIGSAC Conference on Computer and Communications Security)

   A wave of alternative coins that can be effectively mined without specialized hardware, and a surge in cryptocurrencies' market value has led to the development of cryptocurrency mining ( cryptomining ) services, such as Coinhive, which can be easily integrated into websites to monetize the computational power of their visitors. While legitimate website operators are exploring these services as an alternative to advertisements, they have also drawn the attention of cybercriminals: drive-by mining (also known as cryptojacking ) is a new web-based attack, in which an infected website secretly executes JavaScript code and/or a WebAssembly module in the user's browser to mine cryptocurrencies without her consent. In this paper, we perform a comprehensive analysis on Alexa's Top 1 Million websites to shed light on the prevalence and profitability of this attack. We study the websites affected by drive-by mining to understand the techniques being used to evade detection, and the latest web technologies being exploited to efficiently mine cryptocurrency. As a result of our study, which covers 28 Coinhive-like services that are widely being used by drive-by mining websites, we identified 20 active cryptomining campaigns. Motivated by our findings, we investigate possible countermeasures against this type of attack. We discuss how current blacklisting approaches and heuristics based on CPU usage are insufficient, and present MineSweeper, a novel detection technique that is based on the intrinsic characteristics of cryptomining code, and, thus, is resilient to obfuscation. Our approach could be integrated into browsers to warn users about silent cryptomining when visiting websites that do not ask for their consent. 

   more » « less