Index Research
Digital Assets
Case Study: The origins of the Digital Asset Taxonomy System (DATS)

Case Study: The origins of the Digital Asset Taxonomy System (DATS)

Doug Schwenk, CEO of DAR, discusses why there was (and still is) a pressing need for a Digital Asset Taxonomy System and the approach that was taken to ensure that it was robust enough for institutional investors and the investment industry


In 2017 during the initial Coin Offering (ICO) boom, the number of digital assets went from dozens to thousands seemingly overnight. The rapid proliferation of digital assets meant that new ones were being launched daily. This made it difficult for institutional investors to gain access to a broad view of the industry.

At that point, Digital Asset Research (DAR) built an initial taxonomy system to help institutional investors assess this new fragmented asset class. DAR’s goal was to help institutional investors filter data by developing a system much like the ones used in traditional finance but uniquely crafted for the complexities of crypto and with the quality that institutional clients require.

The Digital Asset Taxonomy System (DATS) tracks more than 10,000 digital assets and classifies over 1,300 into a transparent hierarchical structure. The framework allows institutional investors to see sector trends, determine how those trends impact a portfolio, and understand how sector(s) contribute to performance. From there, institutional investors can identify opportunities and risks to build a portfolio in line with their strategies.

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