Have been reading through bullish tweets about @Blast_L2

Imo it’s okay to be a speculative play, but not my conviction bet. Here’s why: TLDR:
- it has existential risks by placing heavy reliance on @MakerDAO & @LidoFinance
- staking reward will be reduced in the future, and Lido could be further affected somehow
- the way of generating native yields on L2 could be easily followed by current L2 market leaders

This 🧵is about what @CelestiaOrg actually does, in view of a voting launched by @DefiIgnas and @VitalikButerin's recent article about @ethereum L2s

To begin with, we need to know what data availability is. Data availability refers to the ability of nodes in the network to access and verify the data associated with transactions and blocks.

Celestia's objectives:
– To make the blockchain networks more decentralized, by solving the problem of state bloat, i.e. as the state of blockchain grows with more and more transactions, the cost of running full nodes is higher due to higher hardware requirement for downloading more data, leaving only more well-equipped full nodes in place and thus the networks more centralized
– To improve TPS by allowing much larger block size for each block: to avoid centralization, there is often a limit imposed on the block size which compromises throughput/ scalability

TLDR: if I understand it correctly, @CelestiaOrg could provide a solution to the impossible trinity of blockchains: decentralization, scalability and security, by allowing sovereign roll-ups to be scalable yet decentralized through using it as the DA layer

Mechanism in details:
Consensus nodes produce blocks
—> Full nodes verify the block content by downloading all block data to produce fraud proof for light nodes; light nodes can’t verify but simply keep track of block headers (summary of block data) and work based on fraud proof
—> As the state of the blockchain (information necessary to execute all transactions) grows with the scale of the blockchain, it becomes more costly to run a full node, since more and more data has to be downloaded in order to produce fraud proofs for light nodes to work, or else light nodes will get tricked by block producers to follow a wrong chain by accepting an invalid block
—> Most chains limit the rate at which their state grows by imposing a block limit, or else the requirement of running full nodes will be more stringent over time
—> With DA modularization (e.g. @CelestiaOrg), light nodes allow full nodes to produce fraud proof WITHOUT downloading all block data each time, since full nodes can simply recapture the full block data now after combining all random chunks of data requested by each light node from block producers via Data Availability Sampling (DAS) which relies on a data protection technique called erasure coding
—> With DAS, the more the light nodes, the higher is the block size limit as full nodes are now assisted by more light nodes which altogether can request a larger amount of random chunks of data from block producers
—> Even with the same computation capacity of full nodes, the larger the block size, the more the transactions are processed by each block, the more efficient the blockchain is and thus the low gas fee is required in peak hours as the congestion can be largely alleviated by more and more light nodes joining the DA layer

Advantages:
– To align scalability with decentralization: with more light nodes, the block size limit is higher, i.e. more transactions can be processed per block with same computation power
– To avoid gas spike at peak times, as congestion is alleviated with better TPS by way of allowing a larger block size for each block

Question: how much scale can @CelestiaOrg offer?
- DAS key property: the more data is collectively sampled, the same probabilistic availability guarantees can be provided for larger sums of data, so that blocks can be made bigger (i.e. support a higher TPS) with more nodes participating in the sampling process
- Tradeoff: the block headers grow in proportion to the square root of the block size; light nodes looking to have almost the same security as a full node's bandwidth costs vary with (√n, n = block size)

2 factors of scalability:
i.) How much data can be collectively sampled: the block size can go much higher as DAS can be performed by a large audience with limited resources (even a smartphone can do it!). Thus one can fairly expect the number of sampling nodes to be correlated with user demand, defining blockspace supply as a function of demand. As it can offer low stable fees as the user demand grows, state bloat issue can be relieved
ii.) Target block header size of a light node grows in proportion to √n (n = block size): likely offset by improvements in network bandwidth over time as per Nielsen’s Law of Internet Bandwidth – if bandwidth capacity of light nodes grows by X, Celestia’s DA throughput can grow by X^2 @CelestiaOrg @DefiIgnas @VitalikButerin @ethereum Feel free to correct me if I have any misunderstanding!
@musalbas @jadler0 @nickwh8te @JoshCStein @ercwl @Cryptocito @Jskybowen @0xCygaar @dferrersan

Main issue in LSD: decentralization vs APR maximization
By making validator set permissionless (vs whitelisting like @LidoFinance), $ETH staked in the protocol may be idle and not fully utilized - eg $rETH APR always < $wstETH APR

@fraxfinance's $frxETH v2 solves it
🧵👇👇 @LidoFinance @fraxfinance 1. What @fraxfinance does in $frxETH v2 is to make staking reward to stakers as lending rate, whereas allowing anyone to be validators, who are the borrowers of $ETH staked in @fraxfinance, by putting 4 $ETH as collateral in case of slashing.

LSD = another form of lending market

A🧵to explain the set up of this new $crvUSD/ $fFRAX pool in the midst of @CurveFinance’s biggest potential crisis

TLDR: the objective is to decrease CRV/FRAX lending pair utilization rate (UR) & interests charged on him by Fraxlend

But why Fraxlend specifically?
👇👇 @CurveFinance 1. Because there’s a Time-Weighted Variable Interest Rate (TWVIR) which adjusts interest over time (max=10,000%) - the higher the UR, the shorter the half-life (12 hours at 100% UR) that doubles the interest.

Can you imagine one day you can get rewarded to do trades/ swap token assets?

@CurveFinance nailed it: traders are now charged with NEGATIVE FEES on LLAMMA!

Curve has reversed the law of mechanics and GRAB more TRADING VOL via the grand scheme of launching $crvUSD

🧵🧵👇👇👇 @CurveFinance 1. TLDR 1: $crvUSD turns demand of leveraging with a reduced risk of hard liquidation into rewards paid to traders who facilitate (de)liquidation when swapping on LLAMMA.

It renders gas optimisation and fee reduction as ways of DEXes to seize vol from aggregators less meaningful

[🧵@CurveFinance is printing money🧵]
$crvUSD is now charging on average >7.5% interest rate on borrowers, but still they are willing to do so, as a way of holding the leveraged long blue-chip - $BTC/ $ETH, without suffering from the risk of hard liquidation

More details👇👇

@CurveFinance 1. $crvUSD maintains its peg via its dynamic interest rate and Peg Keepers (similar to @fraxfinance's AMO) which maintain the peg by minting or burning $crvUSD in its AMM pools.

🧵about one of the most important updates of @CurveFinance (apart from $crvUSD): Tricrypto New Generation (TNG)

TLDR: Curve could FLIP @Uniswap's trading volume as TNG offers better execution price than Uni v3 by optimising gas, drawing huge vol from bots & aggregators

👇👇 @CurveFinance @Uniswap 1. This thread will be split into 2 parts -

i.) [2]-[14]: how TNG update can potentially facilitate @CurveFinance to outperform @Uniswap in volatile asset trading, by optimising gas fees

ii.) [15]-[22]: recap of Curve v2 mechanism and comparison with Uni v3's CLMM

This 🧵is about 3 key issues in DeFi lending. If they are solved, it can unlock super huge upside of DeFi by attracting TRILLIONS of USD from institutions!

They are:
1. interest rate isn't stochastic
2. utilization-based lending is inefficient
3. credit risk isn't composable

👇 1. Implications of 3 issues:
Fixed income, insurance, IR market... things related to risk pricing can't come to fruition without institutional money, as institutions don't know how to price those risks when this market differs much from the existing institutional money market.

A short recap about sell pressure of $ETH after Shanghai upgrade/ Capella:

TLDR:
- worst-case: sell pressure = ~3.4% $ETH daily trading volume, lasting for 5 days, assume all validators choose partial withdrawal (PW) and sell all $ETH reward at once (accumulated since 2020)
🧵👇 1. There are 2 kinds of $ETH withdrawal:
- Full withdrawal (FW): validators removing a full node of 32 $ETH from the staking pool
- PW: transferring the excess (>32) $ETH (i.e. staking rewards accumulated since the start of staking function in 2020) to the withdrawal address

Regarding $USDC crisis, it's time to revisit the most stable stablecoin - @LiquityProtocol' $LUSD with:
- 0 governance
- fully decentralized collateral + UI
- instant liquidation
- lower liq. level than @MakerDAO
- no loss to holders since launch

How can it achieve all these? @LiquityProtocol @MakerDAO 1. TLDR: 4 limbs for @LiquityProtocol to maintain the peg
- Redemption
- Stability Pool
- Redistribution
- Recovery Mode

After the 🧵, you will know how it can allow a volatile asset to peg with USD, with no further product update since launch but no loss caused to holders!!

As I said:

“Recession is forthcoming:
1. Yield curve inversion of 2yr (3mth)/10yr has always been followed by a recession, no exception
2. Historically there has never been a time where recession did not occur for CPI >5% to come down”

SVB is likely to be the start of recession I mentioned this last late Sept and it is still in play

https://twitter.com/DeFi_Cheetah/status/1574068975197356033

LPs of AMM can never be fully compensated by the trading fee (tx fee), which is a compensation only for LPs' cost of capital; LPs suffer from GAMMA RISKS as well.

This 🧵 will dissect the risk profile of being LPs of AMM, especially important to LPs of @uniswap v3!
👇👇👇 @Uniswap 1. TLDR: providing liquidity to AMM, you are just as an option trader hedging delta dynamically for his long put position, except that he profits from longing volatility, while you take gamma risks without complementary rewards.

I'll start from the basics and you'll understand

🧵@eigenlayer is solving the most important issue in crypto, that is, D-apps' innovation is capped by infra's rate of innovation

Impacts:
- ETH price goes up SIGNIFICANTLY
- Make innovations in infra PERMISSIONLESS, eg more well-designed oracles, bridges, sidechains, etc
👇👇👇 @eigenlayer 1. Key issue 1: rate of innovation at the core layer (eg consensus, sharding, etc) is way lower than that at the application layer, since whereas D-apps are permissionlessly deployable on blockchains, core layer upgrades are only permissioned (eg major upgrades on @Ethereum).

Recently I find a new project that facilitates us to find early hidden gems in crypto!

On-chain AI-powered search engine for the crypto community: @_kaitoai, backed by GPT 3, the tech underneath @OpenAI’s ChatGPT!!!!

👇🏻👇🏻👇🏻 1. Have you ever experienced a headache that information in crypto is so fragmented that they are scattered in different websites and you feel dizzy even with the help of high quality tweets that gather those websites? This is where @_kaitoai comes into play.

🧵Royalties War Deep Dived - @blur_io vs @opensea🧵
This is about how NFT marketplaces makes use of royalties as weapons against each other, and what implications/takeaway I get for DEX wars (i.e. @CurveFinance vs @Uniswap)

👇👇👇 @blur_io @opensea @CurveFinance @Uniswap 1. Background
In view of OS's abrupt policy change that succumbs to challenges launched by Blur, it shows how delicate competitive edges can be if your business in web3 is more consumer-oriented. Next I will go into details about what happened these months

https://twitter.com/opensea/status/1626682043655507969

🧵[$FRAX >>> $DAI]🧵
Why are stablecoins of @fraxfinance & @CurveFinance regulatory-resistant than @MakerDAO? In fact, @MakerDAO is at a much higher risk!!

Short answer: Algorithmic Market Operations (AMO) + token fungibility + principle of protection of property rights

👇👇👇 @fraxfinance @CurveFinance @MakerDAO 1. TLDR: $FRAX via AMO successfully mix its centralised collateral $USDC with other 'innocent' crypto assets. As @fraxfinance hold LP tokens mostly and ERC-20 is fungible, regulators/ @circle pursuant to regulators' requests can't ban exact $USDC held by it, nor ban it outright.

[Curve vs Uniswap - recap]
3 separate 🧵s to elucidate why I think @CurveFinance stands a better chance than @Uniswap to be inevitable in DeFi and crypto in the future.
No new arguments added so far, but in here you will get a more general picture for the debate!

Here we go! @CurveFinance @Uniswap 1. Thank @WinterSoldierxz for giving me a chance to make clear arguments to support my thesis. I will recap my points to refute his latest reply here:

https://twitter.com/WinterSoldierxz/status/1620105987045867523

With my utmost respect, I do not agree with his arguments and will show you why after the recap.

[Curve vs Uniswap part 3]
Thesis: @CurveFinance is better positioned to be the core DeFi infra than @Uniswap

TLDR:
1. $CRV ponzinomics? a MISNOMER
- how inflation can be a scheme in game theory
- $CRV emission formula decoded
2. UniV3 needs stacks = worse cost structure @CurveFinance @Uniswap 2. This is in response to a reply from a respectable DeFi OG @WinterSoldierxz who regularly publishes institutional-grade research. Those who haven't followed him should do it.

For his counter-arguments, refer to his thread:

https://twitter.com/WinterSoldierxz/status/1619054919058857984

In-depth content here we go!

[Curve vs Uniswap part 2]
Why is @CurveFinance better positioned itself to be the core DeFi infra than @Uniswap?

TLDR:
1. $CRV tokenomics protects Curve against competition [1-13]
2. Curve’s liquidity-as-a-service: functionalities that solve on-chain liquidity issue [14-19]
... @CurveFinance @Uniswap ...
3. UniV3 loses pricing power by
(i) malfunctioning at extreme market as liquidity dries up outside of LPs' various price ranges [20-22],
(ii) lifting threshold of liquidity management for new projects to set up pools of long tail assets permissionlessly [23-26] & ...

感謝提出觀點，在下反駁觀點如下：
1. 有定價能力的去中心化交易所，MEV volume不會佔大多數的。為什麼？試想像一下套利者為什麼是套利？因為有主要定價的交易所，跟UniV3形成價差，這樣才會產生套利，數據已指出，有43%-60%以上來自於UniV3的成交量都是套利單，這是為什麼？不難理解（Curve只有20%）

https://twitter.com/0x1charles/status/1612846027106836481

2. 這位的觀點忽略了UniV3產生的嚴重問題：LP關係在v3由於能按不同策略提供流動性，這意味著同等的交易費用，聰明有資源的專業LP會把大部分被動和散戶的LP交易費用吃掉，因為前者更聰明
UniV3能提供full-range又如何？這種情況下passive LPs無可觀收益，最終會剩下專業LP，跟orderbook下的MM沒兩樣

This 🧵 is about my analysis framework of DEXes: why I think @CurveFinance prevails over @Uniswap, and why Uni v3 is a wrong move!

In short, 2 reasons: (i) pricing power & (ii) profitability @CurveFinance @Uniswap 1. Background
@DeFi_Made_Here made a thread about @CurveFinance, and a comparison of Curve vs Uniswap.

https://twitter.com/DeFi_Made_Here/status/1611002241674055683

This prompts me to write a 🧵to provide perspectives that not many people will take into account when comparing among DEXes