3/ To get the highest Goo emission rate, first we need to understand that Goo emission is based on:
- Each Gobbler's multiplier
- Goo amount allocated to each gobbler (can be different)
The Goo emission rate will then be `sqrt(m*a)` , where m=multiplier and a=allocation of Goo.
4/ So, here comes the 2 questions: 1. Optimal Goo Distribution -- If you hold certain Goo amount and certain number of Gobblers, how should you distribute them? 2. Goo & Gobbler Pricing -- What should you buy? Gobblers or Goos?
5/ Optimal Goo Distribution
If you hold multiple gobblers (each with different emission multiple), the optimal way to distribute your Goo is to proportionally allocate to each gobbler based on the multiplier.
But why?
6/ Optimal Goo Distribution (cont.)
This directly comes from Cauchy–Schwarz inequality, where the equality occurs at the proportional allocation (a_i) to the multipliers (m_i).
So, given the Gobbler multipliers, you can efficiently allocate your Goos proportionally.
7/ Goo & Gobbler Pricing
The problem is, given $M, how should you spend this to earn the highest Goo emission rate?
To simplify things, we assume things can be bought fractionally:
- $1 can buy `X` multiplier for Gobbler
- $1 can buy `Y` amount of Goo
8/ Goo & Gobbler Pricing (cont.)
If you spend $A on multiplier, you can then spend $(M-A) on Goo.
You'll end up with AX multiplier, and (M-A)Y Goo amount.
9/ Goo & Gobbler Pricing (cont.)
So, your max Goo emission rate (from optimal distribution) = `sqrt(AX(M-A)Y)`, which is maximized at A=M/2 from AM-GM inequality.
This means the optimal strategy is to spend "half" the budget on Goo and "half" on Gobbler multipliers.
10/ Goo & Gobbler Pricing (cont.)
NOTE: This is just a simple model of how you would get the best emission rate given a budget. In practice, Goo & Gobbler price may vary, so use the strat at your own discretion.
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I’ve been interested in Zero-Knowledge Proofs (ZKP) for some time, but it’s quite complex and hard to understand.
So, just wanted to share how ZKP works specifically in @TornadoCash magical blackbox.
🧵👇
2/
Before diving in, let’s start with:
What’s ZKP?
[Wiki] Zero-Knowledge proof (ZKP) is a method for a “prover” to prove to another part (“verifier”) that a statement is true, without revealing any additional information apart from the fact that the statement is true.
3/
There are actually many types of ZKP, including
➡️ Multi-party computation (MPC) – aggregate a result from each party, without revealing each party’s info e.g. finding the total number of patients from each hospital.
✅ Take Long or Short positions on $AVAX or $WETH with leverage
✅ High capital efficiency
✅ Tradeable #StrikeTokens
✅ Earn high APY from liquidity mining 💰💰💰
📈 LONG Strike Tokens: $AVAX-X & $ETH-X
📉 SHORT Strike Tokens: $Y-AVAX & $Y-ETH
These tokens are ERC-20 compatible, and can be supplied & traded on @traderjoe_xyz.
3/ 🔀 Mint & Redeem
➡️ Anyone can use $USDC to **mint** any pair of LONG and SHORT Strike Tokens.
➡️ Anyone can use any pair of LONG and SHORT Strike Tokens to **redeem** the underlying $USDC back.
As NFT holder, selling your favorite avatar is a PAIN with existing tools. You will have to set sell price and wait for buyers.
Worst case = you wait for weeks and keep being frontrunned by other sellers. 😢
On ABW you sell via smart contract at any time.
3/ Why buy on ABW?
Currently to get a hold of trending NFTs, you'll need to keep refreshing the browser until someone decides to sell their bag. If the price is cheap enough then you scoop it up.
NGMI 😔
ABW is a faster and cheaper way to bid for your favorite NFT collections
1/ 📖 Just read @Uniswap v3 whitepaper 🦄 and wanted to share some thoughts.
👀 There are some pretty neat tricks in the paper that we @AlphaFinanceLab also use. 👀
Thread below 👇
2/ Overall, 🦄 V3 is a huge upgrade from and much more complex than V2. V3 introduces:
👩💻 User Flexibility: Users can supply within a specified price range.
💻 Protocol Flexibility: Configurable swap fee & governance fee
💡 Features: Built-in TWAP & liquidity oracle
3/ The most interesting feature is that users can supply liquidity to any desired price range, which then enables the __Concentrated Liquidity__ feature, as advertised.
🤔 This is a challenge in terms of technical implementation, since gas limits may explode if done naively.