Predicting the UST Collapse with DEX Liquidity Pool Data
How to leverage Kaiko’s DeFi data as an early warning indicator
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Terra’s recent collapse is one of many examples showing the growing role that decentralized exchanges (DEXs) play in major market events. In May 2022, the DEX Curve hosted the most liquid market for Terra USD (UST), the Terra blockchain’s USD-pegged stablecoin whose collapse brought down a $60 billion ecosystem. Curve’s UST liquidity pool can thus be considered an essential piece of the story that led to the stablecoin de-pegging.
In fact, market events happening on Curve’s UST liquidity pool could have served as an early warning indicator predicting UST’s demise. Using liquidity pool data, I will show how there was a two-day lag in market activity on DEXs that could have predicted the liquidity crisis that overflowed to CEXs, which ultimately had a systemic impact on the whole crypto-economy.
1. The UST Collapse, in Words
The Market’s Role in UST’s De-Peg
UST’s de-peg was preceded by several major market events that first transpired on DEXs, then on CEXs (centralized exchanges), and finally on the Terra Station. The storyline below focuses on the role of decentralized and centralized markets in UST’s road to 0$, based on facts and observations in the data.
DEXs
This story begins on May 7th, 2022, with Terraform Labs conducting a $150M UST transfer from the UST/3CRV Curve meta pool, to the Curve 4pool. This led to a decrease in UST’s reserves in the UST/3CRV pool and which created a slight increase in UST’s price relative to other USD-backed stablecoins. However, just some minutes later, a smart trader bridged $85M in UST from the Terra blockchain to the Ethereum blockchain and sold those tokens in exchange for USDC using the UST/3CRV Curve meta pool, essentially profiting off of the price discrepancy. Following this massive swap, other very similar trades have been observed in this liquidity pool, leading to a massive UST sell-off and an increase in UST’s market share in the liquidity pool. UST’s price slightly dropped, but there was still hope for UST’s future.
CEXs
4 to 5 days after, the news spread out to retail traders that UST was slightly but consistently trading at a discount to the U.S. Dollar. This led to a quick and massive sell-off on CEXs, leading to UST dropping to $0.7, which triggered a liquidity crisis on major CEXs such as Binance, which saw their order books emptying on the buy side for UST markets. For a more in-depth and data-driven deep dive about UST’s collapse consequences on CEXs, you can read Kaiko’s earlier publication available HERE.
Last Resort Redemptions on Terra
Without any buyers on centralized or decentralized markets, UST holders' solution of last resort was to try to redeem $1 of LUNA by burning 1 UST, whatever its price. However, this redemption could be realized under the single condition that LUNA’s market cap should stay superior to UST’s market cap. As expected, this led to a massive increase in LUNA’s supply and so an even more important decrease in its price on secondary markets due to market uncertainty around the solidity of the Terra ecosystem. LUNA’s market cap ended up dropping below UST’s, causing a “death spiral” and rapid demise of the UST stablecoin to $0.
Now, let’s use DEX and CEX data to visualize this collapse as it played out.
2. The UST Collapse, in Charts
Chapter 1: Early Signals on DEXs
Curve liquidity pool becomes unbalanced.
Curve is a DEX natively built upon Ethereum which mainly provides its users with the possibility to trade tokens of similar value, such as stablecoins or wrapped assets. Thanks to the underlying protocol’s algorithm, Curve has succeeded in providing its users with low price volatility, and a low slippage effect on prices, all this without sacrificing the possibility for liquidity providers to benefit from single-asset exposure, or to carry about the pool unbalances effects on the price.
Liquidity pool reserves, which refer to the number of tokens available in each liquidity pool on a DEX, have a deterministic role in price discovery, thus the ratio of tokens in a pool will affect the price of each token.
Using Kaiko’s liquidity pool snapshot data, we can observe that on Curve’s UST-3CRV pool, after the massive sell-off provoked by a handful of UST holders, UST’s reserves ended up representing more than 60% of the total UST-3CRV reserves, which theoretically could have led to an early UST price de-peg but didn’t thanks to Curve’s pricing algorithm.
Later on May 10th, the situation became even worse, with UST’s reserves in the pool accounting for more than 90% of total volume. We can chart the individual swaps for UST on the DEXs Curve and Uniswap V3 to see how a large number of sell orders quickly unbalanced liquidity pools.
At this point, UST had not yet completely unravelled, showing how DEX liquidity pool and swaps data could have predicted what was to come.
Finally, minting and burning liquidity to a pool can also affect a pool’s reserves. Using mints and burns data, we can see how Curve’s liquidity reserves evaporated after UST crashed by more than 80%. One liquidity provider burned more than 21 million UST from the Curve pool in a single instant, causing an acute liquidity crisis on Curve.
Curve’s Unbalanced UST Pool Was a Leading Indicator.
On Curve, the UST/3CRV liquidity pool was already unbalanced by May 9th. Yet, there was not a massive de-peg of UST’s price, on either DEXs or CEXs. We can thus observe a lag between liquidity reserves on Curve pools and UST price movements, which suggests that Curve’s stableswap invariant (the algorithm that maintains low volatility swaps for stablecoins) had protected UST holders from a massive and early drop in price.
Across all UST markets on both DEXs and CEXs, prices were aligned, despite a lot happening under the hood of these liquidity pools.
This shows that price data was not enough to predict the demise of UST — liquidity pool reserves and mints/burns were essential for understanding what was to come.
Chapter 2: From a DEX Crisis to a Systemic Crisis
The market had a different reaction to both CEXs and DEXs, which we can observe by looking at trade volumes across the two types of exchanges. While on DEXs we observe an all-time high in the traded volume on May 9th, just before the price dropped below 0.9, on CEXs there is a 1–2 day lag on trading volume, which peaked on May 10th and 11th, too late for UST holders to escape from UST’s price de-peg.
Information asymmetry between CEXs and DEXs led to massive losses for the latecomers. UST holders that traded on CEXs seemed to have reacted 1–2 days after UST holders that traded on DEXs when prices had already dropped to 0.8.
Panic spreading on CEXs had an immediate impact on CEX order books, passing on price discovery mode for UST/Stablecoin pairs and once UST’s price reached the 0.7$ threshold, order books began emptying on the buy side for UST.
The Role of Information Asymmetry in UST’s Collapse
Information asymmetry in financial and crypto markets represents a risk for traders. It has been measured and analyzed since markets became electronic in the 90s.
Access to DEX data eases part of information asymmetry and avoids taking unconsidered risks. Altogether, DEX data provided clear warning signals that could have led UST holders to act earlier.
To summarise, the signals identified and described in this article are the following:
- The UST sell-off on Curve on May 7th-8th
- The Curve pools very early imbalance since May 7th
- The 2 day lag between traders' reactions to UST decentralized and centralized markets
3. Takeaways for the Next Crypto Crisis
DeFi has become inevitable to consider, by anyone
The story decrypted in this article concerns blockchains and DeFi protocols among all. However, the consequences are not isolated in the on-chain world, but are real: hundreds of thousands of people have lost all their holdings and sometimes all their life savings, crypto markets as a whole still suffer from this event, even two months after it occurred, and companies went bankrupt.
On-chain & overall crypto markets are not subject to latency
As shown in the charts, UST’s de-peg and snowball effect could have been anticipated in a matter of days. Real-time DeFi data when accessible provides first-comers with a priceless advantage over other market participants. However, what matters the most given how rigid crypto markets still are, is bringing transparency on what’s happening in the markets, at any time, with granular and easily accessible data.
DeFi data relieves pain and generates gains
This data-driven analysis was just an illustration of the power of market data at any stage of the trade process. Such a level of analysis is now accessible to many, for risk management, strategy backtesting, data analysis, or reporting. The charts above are not sophisticated and have been built with raw data and include a small layer of interpretation and intelligence. They can be implemented in a few hours, and generate huge value for anyone. Overall, the cost of adopting and implementing such solutions is insignificant compared to the generated gains.
How to access this data
- Access Kaiko’s DeFi market data: Here
- Download the DEX Data Handbook: Here
- Make an enquiry for Kaiko’s data: Here
To see more from Kaiko and what we have to offer, visit: https://www.kaiko.com/
