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Contribution Details
Type | Bachelor's Thesis |
Scope | Discipline-based scholarship |
Title | Predicting Bitcoin - Gauging the Market for Bitcoin Using Web Search Queries |
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Institution | University of Zurich |
Faculty | Faculty of Business, Economics and Informatics |
Number of Pages | 52 |
Date | 2017 |
Abstract Text | This thesis analyzes the interdependence between search query volumes and the bitcoin price and examines the search query volumes predictive properties to implement a profitable bitcoin trading strategy. A special focus is given to the, by the academic world, neglected and highly influential bitcoin superpower China. The findings of this paper show not only the connection between search-engine data with the bitcoin price, but reveal the anticipatory characteristics of search query data. Thus, allowing for the implementation of market-outperforming trading strategies – supporting the results of prior studies that argue that the bitcoin market is driven significantly by speculation. Chinese search query volumes yielded better anticipatory properties to outperform the market than their counterparts from Google. |
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