Browsing by Subject "Cryptocurrencies"

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Cryptocurrencies: Evaluating the Potential for Adoption in Developed and Developing Nations
(2021-05) Haydon, Parker
I evaluate the potential for the widespread adoption of cryptocurrencies in the United States, Argentina, and Venezuela from five angles: existing state, store of value, the unbanked, perceptions and associations, and regulation. The first factor affecting future cryptocurrency adoption is the existing state which consists of the current adoption--current usage within each country--and national currency performance. The second factor is the potential for cryptocurrencies to serve as a store of value asset while considering hyperinflation and correlation with other assets. The third factor is the ability for cryptocurrencies to help the unbanked. The fourth factor is the perceptions and associations that people have surrounding cryptocurrencies. As with any technology, individuals' thoughts and ideas can significantly impact adoption. Finally, the fifth factor is regulation. Regulation can define how people interact with technologies such as cryptocurrencies. After considering each of the five factors, I conclude that in all three nations, cryptocurrency adoption will likely continue. In comparing the potential for adoption between the United States and Argentina and Venezuela, I determine that individuals in Argentina and Venezuela would be more likely to adopt cryptocurrencies than individuals in the United States based on the five factors analyzed.
Essays on empirical asset pricing and FinTech
(2019-11-20) Shams Moorkani, Amin; Griffin, John M. (John Meredith), 1970-; Titman, Sheridan; Fracassi, Cesare; Johnson, Travis L; Kruger, Samuel; Carvalho, Carlos M
This dissertation studies the determinants of return structure in the cross-section of cryptocurrencies as well as the time-series of market returns during the boom of 2017, the largest known price increase in the history of finance. The first chapter examines the cross-section of cryptocurrencies and hypothesizes and tests that, because of cryptocurrencies' unique features, common demand shocks should be the main driver of the covariance structure of cryptocurrency returns. I proxy for the degree of overlapping exposure to correlated demand shocks using a pairwise “connectivity” measure based on cryptocurrencies' trading locations. I find that this “connectivity” measure explains substantial covariation in the cross-section of cryptocurrency returns. Connected currencies exhibit substantial contemporaneous covariation. In addition, currencies connected to those that perform well outperform currencies connected to those that perform poorly by 71 basis points over the next day and 214 basis points over the next week. Evidence from new exchange listings and a quasi-natural experiment exploiting the shutdown of Chinese exchanges shows that the results cannot be explained by endogenous sorting of currencies into exchanges. Moreover, using machine learning techniques to analyze social media data, I find that the demand effects are 40 to 50% larger for currencies that rely more heavily on network externalities of user adoption. This amplified effect is consistent with the notion that demand for a cryptocurrency not only signals investment motives, but also can be perceived as user adoption that potentially affects the fundamental value of these assets. The second chapter examines the time-series of Bitcoin and the aggregate cryptocurrency returns during the boom of 2017. In particular, Bitcoin and other cryptocurrencies offer the promise of an anonymous, decentralized financial system free from banks and government intervention. Ironically, new large entities have gained centralized control over the vast majority of operations in the cryptocurrency world. One type of these large centralized entities is stable coin issuers who can act as a central bank in the crypto world by controlling the supply of money. This chapter examines the role of the largest stable coin, Tether, on Bitcoin and other cryptocurrency prices. Using algorithms to analyze blockchain data, we find that purchases with Tether are timed following market downturns and result in sizable increases in Bitcoin prices. The flow is attributable to one entity, clusters below round prices, induces asymmetric autocorrelations in Bitcoin, and suggests insufficient Tether reserves before month-ends. Rather than demand from cash investors, these patterns are most consistent with the supply-based hypothesis of unbacked digital money inflating cryptocurrency prices
Essays on open and decentralized business strategies
(2022-08-02) Vasundhara (Ph. D. in information, risk, and operations management); Agarwal, Ashish (Ph. D. in business administration); Barua, Anitesh; Whinston, Andrew; Fracassi, Cesare
This thesis comprises of three essays on the dynamics of open and decentralized business models with the objective to help businesses leverage the most out of such crowd-driven settings. In the first essay, using the context of cryptocurrencies, I assess the impact of sharing IP, i.e., adopting open innovation model, on resulting competition. Open boundaries facilitate copying (also known as forking) the codebase and creating new products, which may compete with the parents for user demand and developer attention. We find that, in spite of added advantage to the parent coins from the installed user base, parents may suffer a loss of demand in the long term due to being copied. However, by adopting a platform model it is plausible for the incumbents to address the negative effects of competition and also attract additional demand. Our results underscore the competitive dynamics of open innovation for demand and development and provide managerial insights for firms assessing open models for product development. In my second essay, again using the context of cryptocurrencies, I investigate whether and how product innovation carried out on the open source platform by a decentralized community impacts users' demand and returns. Moreover, we also assess the decentralized consensus mechanisms such as Proof-of-Work (PoW) governing the production side of a majority of cryptocurrencies. The findings suggest that signals from the open setting and the decentralized consensus mechanism show a significant association with users' demand and returns. In my third essay, I assess the efficacy of a decentralized strategy for content moderation to curb the spread of misinformation. I propose and analyze a crowd-based content moderation approach to fight the spread of misinformation, where users can flag posts they perceive as misinformation, and where such flags become visible cues to other users, and influence their own moderation and sharing decisions. I create a social media application to conduct a randomized controlled experiment, showing users several posts along with social cues such as flags and shares. The results suggest that false posts are more likely to be flagged and less likely to be shared in presence of other's flags. Further, I find that this approach is less likely to affect the sharing of true information. This essay highlights a shortcoming in the current approach of platforms wherein they fail to make use of users' feedback by not sharing it with others and provides managerial guidance for fighting misinformation. Together, the three essays examine and provide managerial implications for firms considering open innovation for, or democratization of, their product development.