Was Terra’s UST Disaster the Canary in the Algorithmic Stablecoin Coal Mine?

The past week has not been easy. After the collapse of the third largest stablecoin (UST) and the formerly second largest blockchain after Ethereum (Terra), the Depeg contagion appears to be spreading further.

While UST has fully detached from the US dollar, trading below $0.1 at the time of writing, other stablecoins also experienced a brief period of losing their dollar peg as well due to the market-wide panic.

Tether’s stablecoin USDT saw a brief depreciation from $1 to $0.95 at the bottom in May. 12.

USDT/USD last week from May. 8-14 Source: CoinMarketCap

FRAX and FEI posted a similar decline to $0.97 on May 12; while Abracadabra Money’s MIM and Liquidity’s LUSD fell to $0.98.

FRAX, MIM, FEI and LUSD price from May. 9 – 15. Source: CoinMarketCap

While it’s common for stablecoins to fluctuate in a very narrow range around the $1 peg, these recent trading levels are only seen under extremely stressed market conditions. The question investors are now asking is: will the fear spread further and will another stablecoin unpeg?

Let’s take a look at the mechanics of some of the major stablecoins and how they are currently trading in Curve Finance’s liquidity pool.

The main purpose of stablecoins is to maintain stable value and provide investors with a way to park their money when the volatility of other crypto assets is much higher.

There are two different mechanisms in stablecoins – asset-backed and algorithm-based. Asset-backed stablecoins are the most common version and issuers claim to back stablecoins with fiat currencies or other cryptocurrencies. Algorithm-based stablecoins, on the other hand, attempt to use algorithms to increase or decrease the supply of stablecoins based on market demand.

Asset-backed stablecoins have been popular during the downturn, with the exception of USDT

USD Coin (USDC), Dai (DAI) and USDT are the most commonly traded asset-backed stablecoins. Although they are all over-collateralized by fiat reserves and cryptocurrencies, USDC and USDT are centralized while DAI is decentralized.

USDC’s collateral reserves are held by US-regulated financial institutions, while USDT’s reserves are held by Tether Limited, which is controlled by BitFinex. In contrast, DAI does not use a central unit but uses the primary market lending rate to maintain its dollar peg, called the Target Rate Feedback Mechanism (TRFM).

DAI is minted when users borrow against their locked collateral and destroyed when loans are repaid. When the price of DAI is below $1, TRFM increases the lending rate to reduce the supply of DAI as fewer people want to borrow, with the goal of increasing the price of DAI back to $1 (vice versa when DAI is above $1 lies).

Although DAI’s pegging mechanism appears algorithmic, the over-collateralisation of at least 150% makes it a resilient asset-backed stablecoin in volatile market conditions. This can be seen by comparing the price action of USDC, USDT and DAI over the past week where DAI along with USDC posted a notable surge on May 12 as investors lost confidence in USDT and rushed to switch.

USDT, USDC and DAI hourly rate. Source: CoinGecko API

Tether’s USDT has long been controversial despite its large market share in the stablecoin space. It was previously fined by the US government for misrepresenting the nature of the cash reserves. Tether claims to have cash or cash-like assets to back USDT. However, a large portion of the reserves turns out to be commercial paper — a form of short-term unsecured debt that is riskier and not a “cash equivalent” as mandated by the US government.

The recent Terra debacle and lack of visibility into their reserves sparked new concerns about USDT. The price reacted violently with a brief depreciation from $1 to $0.95. Although the USDT price has recovered and narrowly downgraded back to $1, the concerns are still there.

This is clearly evident in the largest pool of liquidity on Curve Finance. The DAI/USDC/USDT 3pool in Curve shows a share of 13%-13%-74% respectively.

Curve DAI/USDC/USDT 3Pool share. Source: @elenahoo dune analysis

Under normal circumstances, all assets in a stablecoin liquidity pool should be equal (or almost equal), since the three stablecoins are all supposed to be valued at around $1. But what the pools have shown over the past week is an unbalanced ratio, with USDT holding a much larger percentage. This suggests that demand for USDT is much lower than the other two. It could also mean that in order for USDT to hold the same dollar value as the other two, more USDT units are needed in the pool, suggesting a lower value for USDT compared to DAI and USDC.

A similar imbalance is observed in the DAI/USDC/USDT/sUSD 4 pool. It is interesting to note that both sUSD and USDT rose proportionately around May 12 during the peak of the stablecoin fear. But sUSD quickly got back to the same 25% share and has even declined in percentage since then, while USDT remains the highest share in the pool.

Curve DAI/USDC/USDT/sUSD 4Pool share. Source: @elenahoo dune analysis

The Curve 3pool has a daily trading volume of $395 million and a total locked value (TVL) of $1.4 billion. The 4pool has a trading volume of $17 million and a TVL of $65 million. Both pools show that USDT is even less favorable.

Are algorithmic stablecoins ready?

An algorithmic stablecoin is a different mechanism than an asset-based stablecoin. It has no reserves; hence it is unsecured. The bond is maintained by algorithmically minting and burning the stablecoin and its partner coin based on the circulating supply and demand in the market.

Due to its unsecured or less than 100% collateralized nature, an algorithmic stablecoin is much more risky than an asset-backed stablecoin. The Terra-UST-Depeg debacle has certainly shaken investor confidence in algorithmic stablecoins. This has manifested itself quite clearly in the Curve liquidity pool.

FRAX – an algorithmic stablecoin of the Frax Protocol – is partially collateralised and partially based on the algorithm of supply and demand. Although the coin is partially collateralised, the ratio of collateralised and algorithmic value still depends on the market price of the FRAX.

In the recent perfect storm of stablecoin panic, FRAX’s ratio to the other three stablecoins surged between 63% and 37%. Although the mismatch can already be seen from early March 2022, the collapse of UST has definitely increased fears of FRAX de-pegging.

Curve FRAX/3CRV 3Pool share. Source: @elenahoo dune analysis

A similar surge of fear triggered by the Terra UST de-peg event is also present in MIM – Abracadabra Money’s algorithmic stablecoin. The Curve MIM/3CRV pool shows that the MIM share has increased to 90% – a similar level reached in January when the Wonderland scandal arose.

Curve MIM/3CRV 3Pool share. Source: @elenahoo dune analysis

Despite the algorithmic similarity to DAI, MIM does not use ETH directly as collateral, instead using Yearn Finance interest-bearing tokens (ibTKN) — ywWETH. The added layer of complexity makes it more vulnerable to catastrophic events like the UST Depeg event.

The goal of all stablecoins is to maintain a stable value. But all of them are experiencing volatility and many of them have deviated from the $1 peg much more than expected. This is probably why it has led some regulators to joke that stablecoins are neither stable nor coins.

Nonetheless, the stablecoin volatility is much lower than any other cryptocurrency while still providing a safe haven for crypto investors. It is therefore important to understand the risks embedded in the peg mechanisms of different stablecoins.

Many stablecoins have failed in the past, UST is not the first and certainly won’t be the last. By keeping an eye on not only the dollar value of these stablecoins, but also how they rank in the liquidity pool, investors can anticipate potential risks in a bearish and volatile market.

The views and opinions expressed herein are solely those of the author and do not necessarily reflect the views of Every investment and trading move involves risk, you should do your own research when making a decision.