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dc.contributor.advisorNowostawski, Mariusz
dc.contributor.authorPandey, Dipesh
dc.date.accessioned2022-08-23T17:19:23Z
dc.date.available2022-08-23T17:19:23Z
dc.date.issued2022
dc.identifierno.ntnu:inspera:106263327:65631805
dc.identifier.urihttps://hdl.handle.net/11250/3013123
dc.description.abstract
dc.description.abstractInnovations in cryptocurrency exchanges in recent times have made it easier for people to trade cryptocurrency assets. The increasing number of exchanges has made it clear that this domain will keep evolving in the coming years. Decentral- ized exchanges revolutionized the way we trade cryptocurrencies by eliminating third parties and allowing transparent and open access to all the activities occur- ring on the platform. However, the open nature of such platforms and low barrier to entry have in- creased clutter and noise in the space. In order to understand such anomalous patterns with granular details, it becomes crucial to build tailor-made datasets from the exchanges. Most relevant researches have opted for third-party tools and even paid proprietary resources to obtain data for their analyses. In this re- gard, an empirical method that explores the possibilities of obtaining data from exchanges and using the collected data to perform analyses would be a valuable contribution to the field. Considering the points above, a study was carried out exploring the options of obtaining data from the cryptocurrency exchanges like Uniswap, PancakeSwap, and Binance. Initially, a systematic literature review was conducted that sought out existing research focusing on obtaining data from the exchanges and using it to perform the analyses. The review resulted in very few papers that explored the nuances of data collection. Thus, both the on-premise resources and third-party tools were investigated for data collection to understand the merits of each of them. The collected data was then used to inspect how these exchanges manage their markets regarding pricing, transaction fees, and trading pairs. The results show that using in-premise resources is difficult and tedious to manage but offers incredible speed and flexibility, while third-party resources, despite being slower and expensive, work well when the required data is available. Additionally, the analyses performed show certain areas like usability and fees where Binance does better than Uniswap and PancakeSwap but is comparatively less robust in aspects like transparency and availability.
dc.languageeng
dc.publisherNTNU
dc.titleDecentralized Exchanges: A Qualitative Comparison Against Centralized Exchanges
dc.typeMaster thesis


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