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Feb 8 β€’ 11 tweets β€’ 5 min read
1/11 We simulated LP performance for 21 popular Uni V3 pools (high TVL & volume)

Results were surprising:
πŸ“’ LPs can be profitable!

πŸ’° Which pools made the most?
πŸ“ Are narrow or wide ranges better?

Find out 🧡
2/11 Previously, we explored the ETH-USDC 30bps pool.

For this study:
πŸ—“οΈ Jun 2021 - Jan 2023 (20 months) for most pools
βš–οΈ Daily rebalancing
πŸ“ Narrow (r = 1.05) & wide (r = 1.75) ranges

Here's how other ETH-stablecoin pools compareπŸ‘‡
3/11 Bad pools πŸ˜” (but can you spot the good pool 🐢?)

β€’ ETH-USDC (5bps): -18%
β€’ ETH-DAI (30bps): -14%
β€’ ETH-USDC (30bps): -12%
β€’ ETH-USDT (30bps): -11%
β€’ ETH-USDC (100bps): -9%
β€’ ETH-USDC (1bp): -6%
β€’ ETH-USDT (5bps): -3%
β€’ ETH-DAI (5bps): +7%

(Returns in stablecoin) Image
4/11 We lump some pools together and slap the label "L1/Utility Tokens" on 'em (see legend πŸ‘‡ for pool details)

Good pools:
😊 $MATIC (+66%, narrow)
😍 $LINK (+101%, narrow)
🀩 $ENS (+124%, narrow)

Bad pools:
😦 $WBTC (+2%, wide)
😒 $GNO (-1%, wide)
😭 $BTT (-28%, wide) Image
5/11 Now for DeFi.

Good pools:
πŸ™‚ $MKR (+9%, narrow)
😎 $1INCH (+14%, narrow)

Bad pools:
πŸ˜• $AAVE (-7%, narrow)
πŸ™ $UNI (-28%, narrow) Image
6/11 And NFT/Meme tokens???

Good pools:
πŸ˜… $APE (+28%, narrow)
🀣 $HEX (+209%, wide)

Bad pools:
😢 $LOOKS (-4%, narrow) Image
7/11 For ERC20-ETH pools, returns are in ETH.

Even if we earn 209% in ETH, if ETH price in $ is falling, we might lose in terms of $.

But you can always hedge by shorting ETH! (Panoptic sooon!)

(What if we calculated returns in the ERC20 token...future #ResearchBites? πŸ˜‰)
8/11 Key Insights:

πŸ’€ 7/8 ETH-stablecoin pools underperformed (too popular?)
πŸ† 8/13 ERC20-ETH pools outperformed (not enough ❀️)

Common traits for outperforming strategies:
β€’ Narrow LP range
β€’ Minimal pool price change
β€’ ⬆️ Volume ⬇️ TVL Image
9/11 Caveats:
β›½ Ignores gas/slippage/swap fees
πŸ“ˆ Assumes fees/returns compound day-over-day
⚠️ Past performance is no guarantee of future results!

Questions:
πŸ‚πŸ» What if we LP with bullish or bearish bias?

(Future #ResearchBites πŸ˜‰)
10/11 Disclaimer:

πŸ“’ None of this should be taken as financial advice.
⚠️ Past performance is no guarantee of future results!
11/11 Comment below with questions.

Follow @Panoptic_xyz and @brandonly1000 for more #ResearchBites and other key updates!

Check out our blog πŸ‘‰ panoptic.xyz/blog
Star & follow our GitHub repo πŸ‘‰ github.com/panoptic-labs/…

🀝 Like & Retweet if you found this thread helpful!

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More from @Panoptic_xyz

Panoptic Profile picture
Feb 10
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 πŸ“ˆ

Here's 8 reasons why @Panoptic_xyz is bullish on financial NFTs🧡 Image
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 Image
3/12 Reason 1: Most derivatives in TradFi *are* NFTs

β€”
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. Image
Read 12 tweets
Panoptic Profile picture
Feb 7
1/13 How do you know if one LP position or portfolio is riskier than another?

Is LPing riskier than HODLing?

This is the first of a series of threads where we discuss different types of risk, how to interpret them, and how to hedge them.

Let's dive in!
2/13 Risk measures (RMs) are crucial in assessing the stability and performance of a portfolio, and they can be used to guide investment decisions.

When providing liquidity on Uni V3, there are several key risks to consider such as volatility, market risk, etc.
3/13 Some commonly used risk measures are:

- Beta (Ξ²)
- Value-at-Risk (VaR)
- Conditional Value-at-Risk (CVaR)

All of these measures are related to the volatility of the portfolio. In particular, high volatility typically implies high risk.

Let's discuss them in more detail πŸ‘‡
Read 13 tweets
Panoptic Profile picture
Feb 2
1/12 We analyzed simulated LP performance on ETH-USDC 0.3% pool.

Results were surprising:
πŸ“’ The optimal width was wider than expected.

β€’ What's the optimal width for max returns?
β€’ How does that change for πŸ‚ vs 🐻 markets?

Find out πŸ‘‡
2/12 The strategy is simple:

πŸ’¦ LP around the current ETH price with Β±X% width
βš–οΈ Rebalance your LP position after a day, week, or month (you pick)
πŸ’΅ Collect & compound your fees!
3/12 Our analysis includes >1.5 years of data (Jun 2021 - Jan 2023)

On 5 different range factors:
β€’ Β±5% (r = 1.05)
β€’ Β±20% (r = 1.2)
β€’ Β±50% (r = 1.5)
β€’ Β±75% (r = 1.75)
β€’ ∞ (UniV2 full-range, r = 1000)

Which one did best?πŸ€”
Read 12 tweets
Panoptic Profile picture
Feb 1
1/12 In this series, we will look at different (financial) Greeks.

Most know about alpha, but what about beta? How can we compute it? How can we use it to hedge our investments?

Let's discuss! πŸ§΅πŸ‘‡
2/12 First things first:

Beta (Ξ²) measures the risk of an asset or portfolio, S, against the risk of a reference market index, M.

See the mathematical definition belowπŸ‘‡πŸ€“

Ξ²(S; M)= correlation(S; M) x volatility(S) / volatility(M) Image
3/12 Beta increases w/correlation & relative risk (ratio of volatilities).

How can we interpret this? If:

- Ξ² = 1.5 β‡’ The asset S incr. 1.5% for each 1% incr. in the index M

- Ξ² = 0.5 β‡’ S incr. 0.5% for each 1% incr. in M

- Ξ² = -1.5 β‡’S decr. 1.5% for each 1% incr. in M
Read 12 tweets

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