TY - JOUR T1 - Cryptocurrency Sectorization through Clustering and Web-Scraping: Application to Systematic Trading JF - The Journal of Financial Data Science SP - 158 LP - 179 DO - 10.3905/jfds.2021.1.080 VL - 4 IS - 1 AU - Babak Mahdavi-Damghani AU - Robert Fraser AU - James Howell AU - Jon Sveinbjorn Halldorsson Y1 - 2022/01/31 UR - https://pm-research.com/content/4/1/158.abstract N2 - Although they are 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–short strategy. ER -