Cryptocurrency Sectorization through Clustering and Web-Scraping: Application to Systematic Trading

Babak Mahdavi-Damghani, Robert Fraser, James Howell, Jon Sveinbjorn Halldorsson
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引用次数: 2

Abstract

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.
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通过聚类和网络抓取的加密货币部门化:在系统交易中的应用
尽管它们是作为一种假设提出的,但作者讨论了导致加密货币作为一种合法的新资产类别崛起的历史事件。他们还讨论了围绕加密货币基本面的问题,以此作为解释股票或大宗商品等其他资产类别缺乏板块的一种手段。为了解决这个问题,他们提出了一种新的方法,该方法基于k-means和分层聚类的混合方法,并使用从网络抓取中收集的替代数据。然后,作者重新引入了两个数学模型,即风险平价和动量。最后,他们通过使用风险平价的只做多策略来测试他们的地缘政治假设,并通过多空策略来测试他们的抽象部门化。
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