Surplus-Capturing AMM Study Results

[0xEvan]

@AndreaC

One important point, which is mentioned in the report but requires further discussion, is that CoW Swap uniform price vector is realizable, but it may be biased. The reason is that Cow Swap will look for the best deal for its users. So, for example, if in a given batch, many users want to purchase ETH, then among the many realizable prices, CoW Swap will return the one with the lowest price for ETH. If, instead, most users want to sell ETH, CoW Swap will return the highest realizable price for ETH. On average, the Cow Swap prices may be close to that of an oracle (say, Chainlink). But in each batch, they diverge in a way that depends on the trades that need to be executed. We believe this is an important point to keep in mind whenever using CoW Swap prices instead of a traditional oracle price: the oracle price may be “unbiased” but perhaps unrealizable, while CoW Swap prices are realizable but usually biased.

Our initial study only focused on the most liquid pair ETH/USDC. Perhaps for more illiquid tokens that do not have a chainlink oracle, the bias would be more pronounced. I also suspect that the more illiquid tokens in a batch, there will be more volatility in the asymmetry of slippage as discussed in CIP-17 here.

However, it’s not clear to me how well the initial study results will hold when considering the gamut of liquidity in on-chain tokens and whether this is something that should be embraced or discouraged. Does COW want users to trade tokens like PEPE through the original Uniswap pool or through COW? I would argue the answer is yes because illiquid tokens leak a disproportionate amount of MEV compared to more liquid tokens.

@AndreaC

Finally, several strategic considerations exist around if and how solvers can access feedlot (i.e., the AMM using CoW Swap prices). The issue is that solvers are the ones who ultimately establish CoW Swap prices, which may imply that solvers can name the price at which they can trade on feedlot. The authors acknowledge this issue and propose to address it by changing the solvers’ objective function but never specify exactly how.

What is the strategic relationship between solvers and LPs? From my perspective, solvers are a type of market maker, providing orderflow to LPs at the LP spot price while returning a different price to traders that can deviate from the LP spot price. Currently solvers aim to provide the ‘best’ directional prices to traders to buy low and sell high.

Maybe if solvers compete with each other as LPs on price/volume execution, this could create a sufficient check and balance. Thus if a solver tries to offer a manipulative price to traders, then another solver can offer a less manipulative price to traders and win the auction. The conjecture is that solver LP competition would drive the manipulation incentive to zero.