Analyze the current status of NFT lending agreements from the pricing mechanism and counterparty model.
Written by: Nicole Cheng
Translation: sir
Editors: Sue Tang, Anthony
How to use NFT as collateral for efficient financing? This article introduces the advantages and disadvantages of various methods from two different levels of pricing mechanism (time-weighted average price, user valuation, liquidity pool valuation) and counterparty model (point-to-point, point-to-pool). Provides readers with an introductory introduction to pricing a highly volatile and illiquid asset.
In the past year, we have all witnessed the magnificent development of the NFT field, but we are also aware of a fact that cannot be ignored: when our portfolio has more NFTs, the less liquidity it has. When the rapid development of NFT technology brings more and more novel applications, the demand for financialization of NFT to improve capital efficiency is also increasing.
NFTs are an illiquid asset much like real estate. In the traditional field, real estate is usually used as collateral for loans, and users can mortgage their assets to obtain loans. We can think of loans backed by NFT as collateral for home mortgages, where users can lend or borrow funds by using these illiquid assets as collateral for the loans they make. The intermediary that facilitates this process is known as the NFT Collateral and Lending Protocol. In this report, we focus on the research surrounding such agreements, including pricing mechanisms and different types of approaches based on parties.
An NFT that satisfies collateral requirements needs to form enough consensus around its value to the point where the mainstream believes its value won't fade anytime soon. This requires high transaction volume and a good reputation of the creator, both of which are indispensable. Some of the most recognized NFT collaterals include CryptoPunk, BAYC, MAYC, Azuki, and Doodles, which are also so-called “blue chip” NFT families. If we compare these "blue chip" NFTs to real estate in home loans, they are undoubtedly first-tier cities, and the "blue chip" NFTs with the rarest characteristics are luxury residential areas in first-tier cities.
However, NFTs are highly volatile assets, and even "blue chip" collectibles can fluctuate wildly in value. Before the Otherdeed mint, the floor price of BAYC had hit a record high denominated in ETH, and then there was a drop of more than 50%. A long-term challenge in the design of NFT mortgage lending protocols is: how to unbiasedly determine the value of the underlying asset NFT collateral? Existing players have taken a few different solutions:
https://www.coingecko.com/en/nft/bored-ape-yacht-club
Time Weighted Average Prices (TWAPs)
Oracles like Chainlink can take and publish a time-weighted average of sale prices and floor prices, creating such a mixed price to value NFTs. Such a model can reduce the impact of abnormal events on prices by taking the average of multiple prices within a predetermined period of time, thereby increasing the difficulty of potential malicious price manipulation.
However, using TWAPs in the valuation of NFTs has some major disadvantages: TWAPs can only be applied to NFT products with active markets and high trading volumes, and only such NFTs are less vulnerable to attacks against price oracles. The TWAPs approach is also less capital efficient, as the protocol tends to set a smaller asset collateralization ratio to avoid the impact of extreme market conditions.
Projects using this pricing method include BendDAO, JPEG'd, Drops DAO, Pine Protocol, DeFrag.
User Valuation Method
In the user valuation method, the pricing of NFT is based on the price prediction given by the user. This way of allowing users to make valuations can be applied to a wider range of NFT collections, because it does not require very strict restrictions on the quality of NFTs like TWAPs. Fairer price discovery for NFT can be achieved by incentivizing individuals or curatorial committees. However, this valuation method needs to reward the appraiser, its valuation cost is significantly higher than other methods, the process efficiency is low, and the result may be inaccurate.
Projects using this pricing method include Taker Protocol, Upshot V1.
One of the most important problems with the liquidity pool valuation method user valuation method is that it cannot provide real-time prices for NFT. This problem does not exist in the liquidity pool valuation method. In this approach, every NFT put into the protocol is actively traded by active lenders in the pool, resulting in a constant spot pricing on the NFT equal to the total ETH in the pool. Once the NFT is locked in a pool by borrowers, traders can start depositing ETH into the pool to bring the NFT to what they think it is worth. If the NFT is overvalued in the case of a public auction, traders may lose their ETH; if the NFT is undervalued, traders will put ETH in the pool to fill the pool until they think the true market value of the NFT is reached, in an effort to make a profit on the sale. By encouraging traders to speculate in the NFT pool, the valuation of NFT will become more accurate through such a dynamic method.
Projects using this pricing method include Abacus.
While some of the examples above fall outside the scope of NFT lending protocols, these pricing mechanisms play a vital role in determining loan amount caps and determining whether collateral is liquidated. Once the value of NFT is determined, these agreements can be divided into two models according to the type of counterparty:
peer-to-peer lending
This method is theoretically applicable to all NFTs, and it is easier to reach a consensus on the value of NFTs. Think of it as an open market, with the lending protocol acting as an accelerator for deal formation. One side is that NFT holders can create loans with the terms they want, and the other side is that funding providers can browse the platform to decide who they want to lend their money to. Once the loan offer is accepted by the fund lender (aka the fund provider), the lending protocol will create a smart contract, and the NFT for collateral will be sent to an escrow account guarded by the protocol. At the same time, the agreement will transfer the loan to the borrower together with the NFT exchange note (used to redeem the NFT).
When both borrowers and lenders agree on terms such as the term of the loan, LTV, and annualized rate of return, systemic risk can be mitigated because defaults only occur between lenders and borrowers of a single order. However, with such customizability comes poor liquidity and scalability, as borrowers and lenders need to wait for matching to reach a common agreement.
Projects using this counterparty model include NFTFi, Arcade, MetaStreet.
Peer-to-pool lending
This is a more "market" approach than a "quote-ask" loan deal that may never be reached. In this way, the liquidity funds provided by the lenders will be pooled together to form a pool of funds to share the interest repaid by the borrowers. The calculation of the specific interest depends on the situation of the supply and demand sides. If the borrower fails to repay the loan, or if there is a liquidation problem caused by the price drop of the NFT, the agreement will automatically auction the NFT and return the income to the lender.
Through the method of peer-to-pool lending, the total amount of loans that can be provided can be significantly increased. Borrowers can immediately obtain funds by staking NFT without waiting for lenders to confirm the terms of the agreement. However, this also means that the terms of the loan agreement need to be automatically generated through the oracle machine to generate a reliable price feed. Therefore, this method can only be applied to mainstream NFT products, and long-tail NFT assets are easily affected by price manipulation.
Projects using this counterparty model include JPEG'd, DeFrag, BendDao, MetaLend, Pine, Drops DAO.
For the sake of comparison, I have listed the following table, including some important indicators when evaluating NFT lending protocols. Some protocols decide to place a cap on the collateralization ratio (LTV) to limit the possibility of default. For NFTs with greater liquidity and demand, the ratio is usually higher. In terms of the range of NFTs covered, different protocols vary greatly, but peer-to-peer protocols are better than most peer-to-peer protocols. Note that most protocols are constantly increasing the range of NFTs they support while adjusting their pricing mechanisms and LTV ratios.
Although there is a lot of controversy surrounding NFT mortgage lending agreements, we expect more NFT lending and financialization products to enter the space, providing NFT collectors with a way to unlock greater value from digital collectibles. Going one step further, if one day a sustainable number of NFTs are locked in lending agreements, these agreements may become a certain degree of pricing power over NFTs.
" Declaration: This content is only for popular science learning and communication among NFT enthusiasts, and does not constitute investment opinions or suggestions. Please treat it rationally, establish correct concepts, and increase risk awareness. "