Thursday, September 27, 2018

State of Stablecoins report released

Update: the 2019 State of Stablecoins report, which at 140-pages significantly expands on the earlier-2018 report described below, has now been released. Download the full report and slides and read the summary findings blog.

We are very pleased to release our first State of Stablecoins (2018) report, the first comprehensive research study of the rapidly growing world of stablecoins. 

Download the full report and slides and read the summary findings blog.

The approximately 80-page report includes data and analysis on 57 stablecoins (live and pre-launch projects), and over 1,600 data points were collected for the analysis. The report also provides primers on some of the more prominent stablecoins. Some key highlights from the report include:

  • Stablecoins can be broadly divided into two main stability mechanism categories: algorithmic (e.g., Basis) and asset-backed (e.g., Tether), with 77% of stablecoins asset-backed.
  • Live stablecoins have had mixed results to date in achieving price stability, with asset-backed coins (e.g., Tether) generally delivering on their stability promise and outperforming algorithmic coins (e.g., NuBits).
  • Fewer than two-thirds of all stablecoin projects (60%) are building just on Ethereum (ETH), perhaps lending support to growing concerns over Ethereum’s ability to scale its transaction capacity.
  • Asset-backed stablecoins (e.g., US dollar-backed coins like TrueUSD, the second most actively traded stablecoin after Tether) have raised slightly more project funding ($177m) than algorithmic stablecoins such as Basis ($174m), highlighting lingering questions over whether ‘algorithmic central banks’ can ultimately be successful.
  • To drive network effects and achieve price stability, 51% of stablecoins offer some type of profit incentive for users, or ‘dividend’ mechanism, built into the design of the stablecoin system (e.g., ‘seigniorage shares’, transaction fee dividends).
  • Stablecoin designs presented to date all feature trade-offs (e.g., the more decentralized the system, the less confidence in the price stability mechanism).