1/13 Why are some pools good ๐ถ and other pools bad ๐?
The answer comes from breaking down LP profits into: 1. Price changes ๐ 2. Fees collected ๐๏ธ
By comparing LPs to options, we discover parallel insights โ let's explore! ๐งต
2/13 Price changes
โฌ๏ธ Price up: positive return
โฌ๏ธ Price down: negative return
โคต๏ธ Payoff determined by delta (ฮ) & gamma (ฮ) of LP position
Why use options terminology (ฮ & ฮ) for LPs?
Hint: that payoff looks awfully like a short put option!
3/13 Fees collected
โข Determined by theta (ฮ) of LP position
๐ ฮ: Rate of time decay (dV/dฯ)
๐ฐ dV = fees collected
๐ง dฯ = 1 block
โ ฮ = fees per block ๐คฏ
โ Near the money: ฮ > 0
โ Far the money: ฮ = 0
4/13 In TradFi, options selling is more profitable when Implied Volatility (IV) > Realized Volatility (RV)
Can we compare IV-RV for LPs?
Yes! But let's use fees instead of IVs since:
โข Easier calculation ๐งฎ
โข Fees collected โ options premia ๐
โข โฌ๏ธ options premia โ โฌ๏ธ IV
5/13 Results match TradFi!
๐ถ Good pools (green dots): lie below the line, compensated by high fees given volatility ("IV > RV")
๐ Bad pools (pink dots): lie above the line, not compensated enough ("IV < RV")
(Dot values are summed returns from LPing)
6/13 How do price changes and fees affect returns?
Meaning:
๐ช100% ฮ dominance โ fees drove 100% of LP returns
๐ค0% ฮ dominance โ price movement drove 100% of LP returns
8/13 Previously, we found that LPing on $ENS was highly profitable (+124%), but $UNI was not (-28%)
By graphing ฮ dominance next to cumulative returns, we find:
๐ Bad days (negative returns) driven by price movement
๐ฅณ Good days (positive returns) driven by fees
9/13 Breakdown of positive & negative returns confirms that
good pool ฮ dominance > bad pool ฮ dominance:
The good pool also had a higher proportion of good days:
๐คฉENS: 63% (272/433)
โน๏ธUNI: 55% (335/608)
10/13 The good pool's fees made up for its bad payoffs ($ENS):
Fees: 466%
Payoff: -371%
Return: 95%
The bad pool's fees weren't enough to compensate ($UNI):
Fees: 309%
Payoff: -332%
Return: -23%
(All values are summed)
11/13
๐ฃ Key Insights:
1. LP = short option payoff 2. ฮ, ฮ, and ฮ affect LP returns 3. LPs compensated when IV > RV 4. Good days/pools driven more by fees than by price changes
12/13 Disclaimer:
๐ข None of this should be taken as financial advice.
โ ๏ธ Past performance is no guarantee of future results!
1/12 The weekly volume on all NFT trading platforms was $120M last week. This includes BAYC, CryptoPunks, LOOT, Azuki, etc.
But...
$23 billion (yes, with a B) of value was traded on Uni V3 as financial NFTs ๐
Here's 8 reasons why @Panoptic_xyz is bullish on financial NFTs๐งต
2/12 First of all: why is Uni V3 a financial NFT platform?
Liquidity in Uni V3 is deployed under a price range, which means LP positions are non-fungible and can't be tracked using ERC20s
Instead, Uniswap issues an ERC721 to track the funds controlled by each LP position
3/12 Reason 1: Most derivatives in TradFi *are* NFTs
โ
Futures contracts expire at a set date, and each underlying has multiple tickers:
The Canadian dollar futures \6CH3 (exp. MAR-23) is different than the \6CM3 (JUN-23).
Options follow the OSI standard for exp, strikes, etc.
1/12 We analyzed simulated LP performance on ETH-USDC 0.3% pool.
Results were surprising:
๐ข The optimal width was wider than expected.
โข What's the optimal width for max returns?
โข How does that change for ๐ vs ๐ป markets?
Find out ๐
2/12 The strategy is simple:
๐ฆ LP around the current ETH price with ยฑX% width
โ๏ธ Rebalance your LP position after a day, week, or month (you pick)
๐ต Collect & compound your fees!
3/12 Our analysis includes >1.5 years of data (Jun 2021 - Jan 2023)
On 5 different range factors:
โข ยฑ5% (r = 1.05)
โข ยฑ20% (r = 1.2)
โข ยฑ50% (r = 1.5)
โข ยฑ75% (r = 1.75)
โข โ (UniV2 full-range, r = 1000)