Slippage Analysis switching from 50-50 RDNT-WETH to 80-20 RDNT-wstETH pool

For reference, $RDNT token stats (12.20.22):

For simplicity, let’s assume a baseline liquidity of $1M and an ETH price of $1,200. I’ll also use ETH instead of changing to wstETH.

Linearized slippage formula:


Using this formula, slippage would increase from 0.24% to 0.37% for a 1 ETH swap for $RDNT, a 56% increase if the LP size remained the same. But now, there will be no incentives to locking $RDNT, so a portion of locked $RDNT will move to this new LP.

In order to break-even on slippage, $560k additional liquidity would need to be added. This is 5-6% of the $RDNT market cap and with incentivization to move those tokens into an LP, this seems very feasible.

Let’s say the LP doubles, slippage would then decrease to 0.19% or 78% of baseline for a 1 ETH swap. Lastly, let’s say the LP reaches $5M (~half $RDNT market cap), slippage would decrease to 0.07% or 31% of our baseline scenario.

With the heavy incentivization of the LP and much lower impermanent loss, the additional capital attracted will more than offset the price impact changes and on a net basis, will improve liquidity and reduce slippage overall on-chain.

Some additional items to consider:

  1. Using a liquid staking derivative on Balancer would be eligible for one of Balancer’s core pools, with 50% of protocol fees refunded to the LP pool.
  2. LPs also get to take advantage of staked ETH yield on top of the fees earned as an LP.

Nice analysis, best case scenario would be that all current locked rdnt end up in dlp. That way, we could see large buys coming in with minimum slippage.

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Sure! I also believe the scenarios simulated by @CryptoCycles should me more than feasible and therefore slippage not a problem (it would even be reduced) with respect to the current 50/50 Sushi pool. That would encourage big inputs of liquidity with a negligible price impact.

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Great analysis.

Is it possible to calculate the slippage for 50/50 Sushi assuming the same growth in liquidity? Ie to make a direct comparison, since growth in 50/50 should also dramatically improve slippage.

I don’t get how you are computing Bi. You started with 166.7, and I don’t understand where that came from, then you went to 260, 333.3, and 833.3 but what drives this number?

Good catch. Looks like it should be constant for this to make sense.