Liquid airdrops
A lockdrop model with immediate liquidity, using Uniswap
Featured in Token Economy #91 (subscribe here)
Airdrops are coming back in vogue due to the regulatory uncertainty surrounding token sales.
Historically, the v1.0 model of airdropping tokens to random Ethereum addresses has proven to be largely useless. So teams are experimenting with new distribution models, particularly those teams that have raised private rounds and are now more nervous about a public sale despite getting closer to mainnet launch.
Livepeer pioneered Merkle mine, which has been widely dissected. Other teams are experimenting with variations of that ‘proof-of-work’ model. Edgewere is working on a lockdrop, whereby in order to get airdropped the EDG token one will have to lock up ETH into a smart contract for a certain period of time, after which the ETH gets unlocked (effectively giving up the opportunity cost of lending ETH on Compound/Dharma etc). DxDAO are planning something similar.
This post is a rough brain dump about a version of lockdrop that puts the idle ETH at work by leveraging Uniswap, a protocol for automated market making.
It roughly goes like this:
- XYZ tokens available to be distributed are locked into a smart contract
- smart contract can receive ETH contributions for up to a fixed period of time (contribution period)
- after contribution period lapses, smart contract creates a market for XYZ/ETH on Uniswap and uses XYZ and ETH balances as liquidity pool
- ETH contributors can withdraw ETH and XYZ from the smart contract proportionally to their ETH contribution, or keep earning a share of the trading fees from that market.
One potentially interesting aspect of this is the automated price discovery: a market price for the token is established without actually having to sell tokens or design a bonding curve. The total amount of ETH contributed during the contribution period sets the price of XYZ token in ETH terms (a potential issue here is ETH volatility during the contribution period). In that light, it could also work with a series of contribution periods, where the tokens are made available in subsequent chunks. So contributors in the second/third etc periods have a reference point on pricing. [Need to think more about this scenario].
The other interesting implication is obviously the immediate liquidity for the token enabled by Uniswap. In that light, the game theory is particularly intriguing. Many whom I’ve share this draft with raised the point that one would be incentivized to maximise the ETH contribution in order to get as many tokens as possible. However, for this actor to be able to then sell off the tokens and profit s/he would first have to withdraw most of the liquidity from the market, resulting in not enough liquidity to absorb the sale order. Imagine this actors contributed 99% of the ETH, he’d only be able to sell at best ~1% of this stash. Smaller ETH contributors on the other hand, if they knew there was a whale, would rush to sell the token, removing the incentive for whales to maximize contribution in the first place.
A few open questions remain:
- Where would the equilibrium settle, if at all? Is there a chance no one ends up contributing for fear of others selling out before/to them?
- Would the incentives change at all if ETH contributions were confidential until the contribution period lapses, as something like the Aztec protocol would enable?
- On the more technical side, there’s the open question of how to distribute Uniswap liquidity shares back to ETH contributors from the smart contract that owns them. One way to achieve something similar could be for the smart contract to be a DAO agent interacting the Uniswap in the background and granting DAO shares back to the ETH contributors proportionally. Then there would be some governance around managing the liquidity and fees.
- What are the regulatory implications of this model? Needless to say, PLEASE do not take this post as legal advice, I am not a lawyer!
Anyways, this is very rough and many details have not been thought true enough. But I thought I’d share to get some feedback before spending more time on it.
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Thanks for the feedback Spencer Noon, Dillon Chen, Rob Bent, thibauld Favre, Richard Burton, Sowmay Jain, Patrick Mayr.
