Use Cases are micro-interviews created by SCRF’s research team. They’re intended to provide context for laypeople about important developments in blockchain research, and for our researchers to ask questions.
Uniswap is a decentralized exchange that uses an algorithm instead of an order book to determine prices between two assets. Users buy and sell tokens without an intermediary, or they can provide liquidity, earning yield by staking their own capital to create a pool of tokens to be traded between buyers and sellers.
The first version of Uniswap was simple and efficient. The second version, released in 2020, expanded the system to directly trade pairs of ERC-20 tokens, and quickly became the most popular DeFi platform with $34B+ of volume traded in March according to Coin Gecko.
The third version of Uniswap (v3) will be released on May 5th. It allows liquidity providers to implement non-fungible liquidity positions concentrated at custom price ranges. The Uniswap team claims the new design will boost capital efficiency and provide more customizable liquidity.
Questions
The Research Team collected some questions about Uniswap’s latest update:
When a swap is made against a pool how much additional complexity do price-tick and position-specific calculations add? What calculations need to be performed in contract logic to execute a swap now? Are there gas savings or additional costs as a result of the new approach?
Do the gas costs of price-tick logic and operations get passed on to traders when executing swaps now? Does this in any way impact LP returns if there are gas spikes when a liquidity position becomes activated?
Does v3 effectively require LPs to use bots in order to maintain competitive yield? Will LPs perform the same, better, or worse in v3, and in what ways does this depend on how tightly they manage their liquidity? Will it be expensive or feasible for them to re-balance these positions?
v3 has been advertised as up to 4000x more capital efficient. Where does this number come from? Will this be true for most users or lower on average? How does this efficiency translate for trader experience? Is there a cost to more capital efficiency (eg. more variable yield)?