DODO Megascope contains the following sections and content:
Gamefi & NFT
In the past week, the address
0x57e04786e231af3343562c062e0d058f25dace9e used USDC as collateral to borrow CRV from Aave, shorting a total of ~92 million CRV. As a result, the price of CRV fell from $0.6 to around $0.4. According to statistics, this address has sold about 5% of the CRV circulation. Curve founder Michael deposited about 150,000,000 CRV on Aave, accounting for about 28% of the total CRV circulation. The liquidation price of CRV in Aave is around $0.24. Since most of it is owned by the founder of CRV, once the liquidation is triggered, Michael may lose control of Curve. The Curve community spontaneously formed a CRV price defense war, and a large number of CRV supporters began to buy CRV, which once raised the price to around $0.7, triggering the liquidation of loans at the attacking address. Ultimately, the attacker lost about $10 million in Aave liquidations. Due to the lack of liquidity on the CRV token chain, it also left Aave with about $1.6 million in bad debts. This is insignificant for Aave, and the Aave community will currently propose to use Aave Treasury to cover debt losses.
The owner of the loan attack address is @avi_eisen (alias Avraham Eisenberg) who attacked Mango Market before, causing Mango have $100 million loss. Eisenberg is considered a professional market manipulator. In February, he was accused of misappropriating $14 million from Fortress DAO, a project he was responsible for developing. Eisenberg allegedly abused the project’s fund redemption mechanism to redistribute remaining funds to token holders when Fortress DAO ceased operations; in April, an address related to its commonly used address was used to manipulate lending protocol Fuse’s liquidation mechanism. Recently, he also tried shorting USDT, but was unsuccessful.
The occurrence of such extreme events continues to challenge the limits of DeFi products. On the one hand, it disrupts the orderly operation of DeFi products and brings losses to investors or project parties. On the other hand, it also urges project parties to design more robust products.
Almost on the same day that the CRV squeeze was staged, Curve released the long-awaited stablecoin crvUSD white paper.
The core mechanism of Curve stablecoin is the LLAMMA clearing system, which can be considered as an improved mechanism based on the Uni V3 AMM. Taking ETH/USD pool as an example, the Uni V3 range will pend order. When the price rises to the upper bound of the price range, the assets in AMM will 100% converted into USD. When the price drops to the lower bound, the assets are 100% converted Became ETH. That is to say, ETH assets increase and USD assets decrease when the price drops. The difference is that the liquidation mechanism of the traditional lending agreement is liquidated instantaneously after reaching the liquidation price, which will cause large fluctuations in the market and cause liquidation losses. The LLAMMA mechanism aims to make liquidation a relatively slow process by introducing an internal liquidation mechanism. The specific method is: dynamically adjust and divide the price range of AMM, the price boundary pcd and pcu exist as a function of the oracle price p0, and the rate of change is faster than p0.
With the oracle price p0 remaining constant, the AMM works in the normal way, e.g. sell ETH when it goes up and buy ETH when it goes down.
When po rises, because the curve changes faster, the current market price p will be lower than the price under the same balance in the pool, at this time ETH will increase and USD will decrease. In this case, when ETH is expensive, LLAMMA will all switch to ETH, and when ETH is cheap, LLAMMA will all switch to USD.
Price Anchoring Mechanism (PegKeeper)
When crvUSD > 1, the PegKeeper contract mints unsecured stablecoins and deposits them unilaterally into Curve’s Stableswap pool; when crvUSD < 1, PegKeeper will withdraw and burn the stablecoins. It can be noticed that when the price is greater than 1, the minted stablecoin is unsecured. The white paper states that the liquidity in the stablecoin pool at this time can be used as collateral for this part of the excess issued tokens in disguise.
Summary: The liquidation mechanism proposed by Curve has many innovations, but its stability and security have yet to be verified by the market. It is reported that Curve will release an updated version of the white paper in the next step, and Dr. DODO will continue to track the progress of the project.
For more discussions on crvUSD, welcome to listen to our researcher Bruce(@SlimeVerse _)’s opinion in the Chinese Twitter Space organized by 7UpDAO last week:
Four Common NFT Pricing Strategies
Machine Learning Based Pricing
In terms of machine learning, NFT's historical sales and metadata can be analyzed to obtain relatively accurate large-scale pricing.
There are a number of platforms that provide NFT holders with statistical analysis through machine learning to determine the value range of a given NFT. The machine learning aspect can analyze the historical sales and metadata of NFTs to derive the most accurate pricing at scale.
Upshot is a machine learning based NFT pricing platform. It can provide near real-time NFT price information and support a new set of financial primitives. In addition to pricing information, Upshot also provides other data, such as metadata and collection level information.
Time Weighted Average Price (TWAP)
TWAP is a trading indicator that calculates the average price rise and fall of an NFT over a specific time period. Manipulating market prices is made more difficult and expensive by taking the average of various transactions over a predetermined period of time. However, TWAP can only be used for liquid NFTs with high trading volume, and is not suitable for less liquid NFTs.
Peer Forecast Pricing
In this strategy, the creator or NFT owner can let other users evaluate what their token price should be. In other words, it's an artificial valuation. Participants are rewarded for providing valuations, calculated by a "mutual information" index (a generalization of correlation). However, this approach is not very efficient or accurate unless the NFT in question is extremely rare and relevant.
Abacus is a platform that uses peer-to-peer predictive pricing to provide liquidity support for NFT holders and rewards for accurate evaluators. It does so by creating evaluation pools where peers can evaluate NFTs. Thus, it reduces the volatility of the token, benefiting all segments.
Pricing of Derivatives
Many financial verticals surrounding NFTs, such as lending, leasing, and fragmentation, will ultimately affect the asset pricing of NFTs. This is part of the derivatives pricing strategy: providing real-time pricing of NFTs and their surrounding markets by using financial derivatives and auction mechanisms to price NFTs based on its financialization verticals.
Uniswap airdrop analysis: Airdrop was once considered the main method of Web3 project marketing. However, this method is difficult to retain users. Dune analyzed the value of airdrops to the project by analyzing the wallet addresses that have received Uni airdrops.
Modeling the revenue of Ethereum MEV nodes: By backtesting the MEV revenue of miners from 2021.9.1 to 2022.8.30 after the release of EIP-1559, the Monte Carlo simulation method is used to predict the MEV revenue after the PoS upgrade. Conclusion: A validator group will obtain a more stable return than a single validator, and the volatility of the return of a group of 32 validators is about 2.3 times lower than that of a single validator.
WBTC is the first ERC20 token backed 1:1 with Bitcoin, bringing greater liquidity of $BTC to Ethereum. Some stats:
Marketcap : $3.53B
% of total BTC on Ethereum：83.88%
Two key roles & their responsibilities in WBTC:
Custodians: guarding $BTC used for fully-back the issue of WBTC (the only custodian - BitGo)
Merchants: Receiving requests from users, initiating minting newly wrapped tokens and burning wrapped tokens to the custodians.
Alameda Research was excluded from the merchants, but keeps the No.1 ranking with 101,746 WBTC minted and 29,435 WBTC burned. Worth being aware of the huge gap b/w mint and burn.
Daily Mint-Burn last week:
Total Burn-Mint Amount: 15,867
Burn-Mint Amount(Nov.26th): 4,680
Nearly 7% reduction in total supply
Twitter 2.0 may integrate the Signal protocol to launch the encrypted private message function.
Sushi's new CEO: The first draft of the new Token economics has been completed and will be presented internally next week. The encryption community is not optimistic about Sushi's ecological revitalization.
nftperp received $1.7m in seed funding. Dialectic, Maven 11, Flow Ventures, DCV Capital, Gagra Ventures, etc. participated in the investment. The testnet is now interactive.
Across Protocol raised $10m at a $200m valuation. Hack VC, Placeholder, and Blockchain Capital participated.
The Oasys main network has been fully launched in three stages, and the multiverse of games built by many game manufacturers.
Web3 game development company Midnight completed a $7.5 million seed round led by Shima Capital.
Dr.DODO is Hiring: