2/Some say that NFTs “shouldn’t be” liquid, yet the innovation process continues.
Just like photography has become much easier to create in the last 100 years, liquid NFTs will surely bring down price points of tokenized digital content but will also open expansive new markets.
3/The key observation is this: #NFTLiquidity is merely a technical problem for #DeFi, and the entire set of economic mechanisms is its solution space.
👉🏻 In particular, because of tokenization, *the NFT liquidity problem reduces to the NFT price discovery problem.*
4/In other words, if we could reliably price a set of NFTs, we could issue a token backed by their reliably priced future resale value.
This is a core mechanism that today is underutilized in the market, and one that — we will soon see — applies to all illiquid assets.
5/Today, NFT price discovery proceeds via three main mechanisms: sales, auctions, and ERC20 fractionalization.
And the fundamental problem with each of these mechanisms is capital efficiency: in each mechanism, participants need to spend *at least* $N to value something at $N.
6/If we could find a mechanism which could appraise any NFT for a fixed price (or just a low one!) we could achieve capital efficiency, tokenize the value of the assets, and 💥💥💥 boom we are liquid.
7/This appraisal mechanism can essentially be implemented using prediction markets, oracles, appraiser networks, or ML models.
But one super cool approach uses peer prediction oracles created by @nick_emmons and @UpshotHQ.
8/In this model, a “hot or not” game is played by appraisers who continuously compare and rank NFTs. Eventually, this ranking places the NFTs into a partial ordering which can be calibrated to price.
Prices can then be reported on-chain through @UpshotHQ’s mechanism.
10/These kinds of #AppraisalGames will go a long way toward achieving liquidity for the NFT asset class and can extend into other illiquid assets — used cars? Homes?
This is just the beginning but we’re about to go into yet another exciting innovation cycle of #NFTLiquidity.
1/I think we will find in retrospect that decentralized lending protocols and their lending rates are of universal importance not just to #DeFi, but to the entire ecosystem.
2/#Layer2 is coming and in these networks we must capitalize state channel hubs in order to create throughput. This creates a substantial hurdle for running hubs & caps commissions.
3/Instead of locking capital, hub operators might leverage lending protocols to borrow it & increase throughput. However, the borrowing rate will inform the commission hubs will charge (and vice versa).
I am working on a post about decentralized resource networks (think file storage or computation) competing with the unit economics of large, efficient incumbents (think Amazon).
Wow, when you write this stuff out on paper, things get very interesting.👇
We tend to think of networks as monolithic protocols that compete with a large incumbents like Amazon as a unit.
But of course such networks are also coalitions of small-to-medium providers that have agreed to follow the network’s rules in order to coordinate.
What they coordinate on is competing with incumbents on weak points: closedness, privacy, censorship-resistance, customer experience, and of course pricing.
They also compete with each other, eroding their margins to nearly 0. (More on that later.)
First and foremost, if you are designing *governance systems* and you’re not up to speed on our 200+ years of quantitative research in this area, consider researching this body of work.
Here is a resource to get you started, first tweeted in 2017: