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dc.contributor.author | Babanov, Aidar![]() |
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dc.date.accessioned | 2021-05-12T05:43:51Z | |
dc.date.available | 2021-05-12T05:43:51Z | |
dc.date.issued | 2021-05 | |
dc.identifier.citation | Aidar, B. (2021). Trading Data Analysis and Detection of Successful Market Participants in Ethereum Blockchain. (Unpublished master's thesis). Nazarbayev University, Nur-Sultan, Kazakhstan | en_US |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/5384 | |
dc.description.abstract | The modern financial market is very complex, you can buy and sell currencies, stocks, real estate, and much more. It expanded that cryptocurrencies appeared. One big difference between cryptocurrencies and other securities is the ability to track transactions. And if is possible to track transactions, then it is possible to define successful traders. The purpose of this thesis is to determine whether it is possible to find traders who make a profit, how they trade, what their strategy is, and how well they make a profit. The final purpose of this work is to prepare software for future trading based on the findings from the search for traders. The Ethereum blockchain acts as the main ecosystem, and Ether is the main currency. Uniswap acts as a trading platform, which means that we only consider successful traders, who make profit on this platform. Data collection was carried out using open sources of 11 thousand traders and more than 2 million transactions. To filter the data, a primary observation was made of where and what currency is popular among traders, as well as what volumes traders operate in. Based on the results of this analysis, addresses and transactions were identified that could potentially be suitable for further analysis. The main analysis was carried out using a sliding window method and the buy-sell cycles method, which is described in detail in the work. Sliding-windows were applied to find all possible profitable traders at different time intervals, and the buy-sell cycles method was applied for a more narrowly targeted strategy. Software is based on buy-sell cycles analysis, searches for new traders, and tracking their activity on the Uniswap platform. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Nazarbayev University School of Engineering and Digital Sciences | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | Type of access: Gated Access | en_US |
dc.subject | transactions tracking | en_US |
dc.subject | trading data | en_US |
dc.subject | Ethereum blockchain | en_US |
dc.subject | market | en_US |
dc.subject | Research Subject Categories::TECHNOLOGY | en_US |
dc.subject | Uniswap platform | en_US |
dc.title | TRADING DATA ANALYSIS AND DETECTION OF SUCCESSFUL MARKET PARTICIPANTS IN ETHEREUM BLOCKCHAIN | en_US |
dc.type | Master's thesis | en_US |
workflow.import.source | science |
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