@article {Mahdavi-Damghanijfds.2021.1.080, author = {Babak Mahdavi-Damghani and Robert Fraser and James Howell and Jon Sveinbjorn Halldorsson}, title = {Cryptocurrency Sectorization through Clustering and Web-Scraping: Application to Systematic Trading}, elocation-id = {jfds.2021.1.080}, year = {2021}, doi = {10.3905/jfds.2021.1.080}, publisher = {Institutional Investor Journals Umbrella}, abstract = {Although it is presented as a hypothesis, the authors discuss the historical events that have led to the rise of cryptocurrencies as a legitimate new asset class. They also discuss issues around cryptocurrency fundamentals as a means to explain the lack of sectors that exists for other asset classes such as equities or commodities. To address this issue, they propose a new methodology based on a hybrid approach between k-means and hierarchical clustering with alternative data gathered from web-scraping. The authors then reintroduce a couple of mathematical models, namely risk parity and momentum. Finally, they test their geopolitical hypothesis through a long-only strategy using risk parity and test their abstract sectorization through a long{\textendash}short strategy.}, issn = {2640-3943}, URL = {https://jfds.pm-research.com/content/early/2021/12/09/jfds.2021.1.080}, eprint = {https://jfds.pm-research.com/content/early/2021/12/09/jfds.2021.1.080.full.pdf}, journal = {The Journal of Financial Data Science} }