Welcome to the second edition of Fluff and Air, a now-confirmed recurring publication by 0xcarnation and ct_zpy. Today we will fud study our favourite chains! Meow.

Just a heads up: This post is just for education, and this post is not financial nor nautical advice. We may hold tokens of some of the projects mentioned here.

Following the bricking that happened on Fantom and some of the analysis that followed, we wondered how liquid our favourite chains are?

Or put simply, if you were trying to exit the chain with *size*, how rekt would you (and the chain) be?

Spoiler alert - your chain is not that liquid.

Methodology

Market caps were pulled from CoinGecko. TVL was pulled from DefiLlama. The DEXes used to determine slippage were DEX aggregators where possible (like 1inch, Kyberswap, and Jup.ag), or the largest DEX on a chain if not possible. All numbers were pulled between 4/30 and 5/1. We imagine the general ratios between MC and TVL will remain relatively stable, but the underlying data will quickly become stale as prices change.

We checked the slippage when selling tokens that fit into the categories of: primary gas token (gas token of the chain), secondary gas token (gas token of the underlying L1), and governance token of the chain. We examined a total of 17 chains and 23 chain-token combinations.

We attempt to sell the token in question for the most liquid stablecoin on the same chain.

Taking a similar approach to (link to thread), we asked the following Qs:

• What happens when you try to dump 1% of the Market Cap on chain

• What happens when you try to dump 1% of the TVL on chain

• How much dumping will bring slippage up to 50%

Chains were then assigned an “illiquid factor”, which was calculated by dividing TVL by the amount of money required to reach 50% slippage. A really high illiquid factor means that even if a tiny fraction of TVL decided to exit, they would cause terrible slippage and also take away a large fraction of stablecoin liquidity. The naïve interpretation is that high illiquidity factors are bad.

Results

Here is our raw data table:

Here is a visualization of the relationship between the Illiquid Factor and TVL:

You can find a link to the spreadsheet here (and hopefully, we find a better alternative to G-Sheets in the future).

Overall trends

Using the “illiquid factor” metric, Ethereum is ranked 18th among the 23 combinations we looked at. However, the amount of money required to to reach 50% slippage on Ethereum is 1.18B, which is much higher than other chains. The closest chain is BNB with 430m required to reach 50% slippage.

Thus, our “illiquid factor” metric is an interesting, but flawed metric. As the largest chain, Ethereum is obviously the most liquid chain. Most chains are simply incapable of pushing 1.18B in a single transaction, and the few other chains that could would eat much more than 50% in slippage. Perhaps a better way to measure illiquidity would be to calculate the ratio of TVL that is alts vs stables.

Slippage when pushing 1% of TVL is an interesting way to see which chains have a variety of liquid assets. Osmosis and Metis rank at number 1 with 8%. It appears that OSMO/UST and METIS/ETH form a large % of TVL on their respective chains. ETH, SOL, and AVAX respectively have 48%, 37%, and 47%- suggesting that ETH/USDC, SOL/USDC, and AVAX/USDC make up a much smaller % of TVL on their respective chains.

Luna and UST and xDAI

xDAI is a neat case because the native gas token is also a stable coin. The main reason why the illiquid factor is very low because xDAI exists in a Curve pool with USDC, and there is actually negligible slippage until you have heavily skewed the pool ratio. In our opinion, this is an under-appreciated advantage of having a stablecoin gas token.

In comparison, even though UST is also a native gas token as well as a stable coin, there is no exit liquidity in the form of alternative stables (weUSDC is the best we could find) on Terra! A sizeable chunk of UST locked into Anchor as well as dexes across all the chains, and the main UST liquidity exists on Curve on ETH Mainnet.

Funnily enough, when you enter a big number into astroport.fi, it gives slippages of greater than 100%!

Knowing a lot of UST is either not on Terra or not liquid, it makes sense that Luna is illiquid on Terra as well. One caveat, we know that Luna can be burned to mint more UST, so in an emergency, some actors could choose to burn Luna and use UST to buy more Luna.

“Wait! Won’t people just add liquidity back on-chain?”

Maybe! But in a scenario where something catastrophic happens, the chain will be extremely congested, as everyone and their grandma who took out a collateralized loan is getting liquidated.

During this period, the token prices would likely be falling on CEXes, which will cause price feeds to provide lower prices and cause more bricking on-chain as more ppl are now under liquidation risk.

Osmosis

The most liquid pool on Osmosis is the ATOM/OSMO pool, unlike most chains where a stablecoin pool is their most liquid pool. The UST/OSMO pool currently has 222m in liquidity, whereas the ATOM/OSMO pool has 281m in liquidity. This makes the ATOM/OSMO pool about 27% more liquid. That being said, if the price of ATOM and OSMO continues to dump, the UST/OSMO pool will end up being more liquid.

Near

NEAR is more liquid on Aurora than natively on Near itself. We take this to be evidence that EVM-compatibility brings a lot of liquidity much faster than building a native DeFi ecosystem from scratch.

Layer 2s

Interestingly, ETH on all L2s (except Aurora) have better liquidity than on ETH Mainnet. This would mean that unless your size is actually size, you’d get more bang for your buck when converting ETH on a L2 instead of Mainnet.

AURORA is Aurora chain’s governance token, and doesn’t have much utility yet. AURORA on the Aurora chain is very illiquid. We might expect the same to happen when/if to other L2 governance-only tokens (looking at you, Optimism and Arbitrum).

In comparison, BOBA is actually very liquid, considering it is also just a gov token. We attribute this to the fact that Oolongswap on Boba actively incentivizes LPs for the BOBA/USDC pool, while the the incentives to LP AURORA/USDC is lower.

Not too surprisingly then, ETH on Boba and Aurora is much more liquid than the L2 gov tokens themselves (BOBA and AURORA).

What else can we do with this analysis?

• For a more comprehensive detailing of how much exit liquidity there is on-chain, we could calculate the % of TVL that belongs to volatile tokens vs stablecoins.

• With only a single time point in our dataset, it’s hard to interpret exactly what the implications are. So we could track the change in this ratio over time as a chain develops an ecosystem.

• We could also investigate the change in “illiquidity” around certain large events. Does the liquidity ratio improve in a bull or bear market? Or when an ecosystem implements various changes (EIPs, gov proposals, new tokenomics, etc).

• On-chain stop-loss hunting, guided by the total stable liquidity as a means to gauge where to trigger a liquidation cascade. Malevolent actors could use these metrics to guide their approach to bringing down the chains they don’t like.

This concludes the second edition of Fluff and Air. Meow~