Part 2: Quantitative Crypto Insight: Stablecoins and Unstable Yield

By George Liu and Matthew Turk

Tl;dr: This blog analyzes centralized stablecoin lending yield for Compound Finance and shares our insights on performance, volatility, and factors that drive this yield on collateralized lending of stablecoins in DeFi. The analysis shows that this lending yield can outperform the risk-free yield in the TradFi market.

In part two of this quantitative research piece, we will examine stablecoin lending yield for the Compound Finance V2 decentralized finance (DeFi) protocol and share our insights on yield performance, volatility, and what factors are driving yield on collateralized lending of stablecoins through DeFi protocols. We also compare the “risk-free” yield in traditional finance (TradFi) to the concept of “low-risk” yield in DeFi, which we introduced in part one.

ACKNOWLEDGEMENT: While we are aware of the recent collapse of Terra’s algorithmic stablecoin TerraUSD (UST), our analysis here is on the area of collateralized lending yield for centralized stablecoins. We’re focused specifically on Compound for USDC and USDT (fiat-backed stablecoins), which have disparate risks and opportunities.

We conclude in this piece that using stablecoins for low-risk (within DeFi) collateralized lending could outperform the risk-free investment in the traditional financial market.

USDT/USDC Yield Analysis

As mentioned in from the 12 period EMA — in this case on price) as it could help momentum investors to decide when to leverage and when to deleverage.

We see a noticeable increase in R-Squared scores, as both USDC and USDT got a bump to a level around 60%-70% as shown below.

From this data we can conclude that stablecoin supply is a substantial contributing factor, as it alone is able to bring the score to around 60% for both stablecoins in any of the two markets. It seems to suggest that [supply] is a major factor in affecting the yield in the stablecoin lending market. This is very similar to the TradFi world, where credit supply by the Federal Reserve will affect the general interest rate of the whole system.

The introduction of MACD data (on BTC and ETH price) brings mixed improvement. In the case of the BTC market, its independent contribution is far less than the supply factor, and the marginal benefit over the shoulder of supply is only a few percentage points. We noticed in the ETH market, however, that MACD has a greater independent contribution to the R-Squared value as compared to the BTC market. This suggests that stablecoin lending yields are more correlated with momentum based trading activity in ETH than in BTC.

An example of the regression coefficients for USDC lending yield in the ETH market are displayed below. The table suggests that higher ETH prices, volatility and [stable coin supply] are generally associated with lower USDC lending yield. At the same time, the stronger the MACD signal is, the higher the yield would go.

Comparison to the Traditional Risk-Free Yield

While it is interesting to reveal what has driven the low-risk yield on stablecoin lending, it is also important to compare these yields with the counterpart in the TradFi market.

Because stablecoin lending yields are derived from the realized floating interest rates for collateralized loans on the Compound platform, we selected the

The analysis makes use of the Compound v2 subgraph made available through the Graph Protocol. Special thanks to Institutional Research Specialist, David Duong, for his contribution and feedback.

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Part 2: Quantitative Crypto Insight: Stablecoins and Unstable Yield was originally published in The Coinbase Blog on Medium, where people are continuing the conversation by highlighting and responding to this story.