Greetings community,
Today I want to surface an idea that has been brewing on my mind for quite some time. One of the most infamous tensions that exists is surrounding DEX emissions. There are quite a few pieces to take into consideration, so let’s first go over the players.
- Liquidity providers for asset 1…n
- Traders for asset 1…n
- External protocol emissions behind asset 1…n
- Qualification of risk for asset 1…n
The ultimate goal of emissions is to create a liquidity supply environment that properly matches demand. Pay for too much liquidity, it goes unutilized. Pay for too little liquidity, you won’t attract trading activity. Most DEXs try to focus on mastering this balance.
However, I have a different thesis. I think overoptimizing for the above neglects the most important part of any decentralized exchange - the partners. If I am an external token coming to a DEX, what am I optimizing for?
- Exposure to traders
- Marketing
- Liquidity that gets utilized
The overlap is quite tight on these. However, DEXs often are overly cautious on partners and are undervaluing new projects with respect to how much external capital emissions the partner is paying to attract TVL and users.
If a DEX only optimizes everything based on volume, they are ignoring the risk that external partners are taking when they take a leap of faith of putting their external capital emissions on said DEX versus a competitor.
As such, I would propose the following change to incentive distribution as well as formula which will optimize for a consistent free market competition that values not only the volume partners bring, but also recognizes the value of the capital they are committing to ShadeSwap as well (regardless of volume results).
Current monthly category emission gauges:
- StableSwap | 4,813 SHD | 18.71%
- Derivative Onramp | 5,479 SHD | 21.30%
- SILK CPMM | 11,460 SHD | 44.54%
- Shade Pair | 3,975 SHD | 15.45%
I would propose a change to the following:
- StableSwap | 5,145 SHD | 20%
- Derivative Onramp | 5,145 SHD | 20%
- SILK CPMM | 7,718 SHD | 30%
- Shade Pair | 7,718 SHD | 30%
This shifts ShadeSwap emissions to be more focused on Shade pairs and the StableSwap as opposed to purely SILK CPMM pools. Derivative curve is already an extremely efficient onramp with the best performance in Cosmos - the lead on this is significant so we don’t need to “double down” on spending on it. Taking advantage of the derivative efficiency means spending less on the category, not more.
Now, a key piece in the puzzle is moving away from protocol-to-protocol BD deals. In the current form, we approach a partner and iterate back and fourth on terms. This is less data and less free market driven because we were working on getting partners in the door as opposed to empowering the partner to enter the door on their own while being fairly graded.
I would propose that we fully change over to a data driven model where partners are incentivized to bring as many incentives as possible + as much volume as possible. In the current form of DEX incentive models, DEXs are too hyper focused on volume and not focused enough on recognizing the risk the partner capital is taking on. As such, I would propose the following formula to score each pool:
X = 30D average volume
Y = Volume Bias
Z = Total Category 30D Volume
A = Total $ External Incentives 30D
B = Capital Bias
C = Total $ Category 30D External Incentives
S = Total Scores Across Category
T = Total Category SHD Incentives
((Y * (X / Z) + B * (A / C)) / S) * T
Example with two projects ZETA & ALPHA both in the StableSwap category. A volume bias of 60% will be chosen so as to favor the significance of volume over the significance of external incentives.
ZETA:
X = $500,000
Y = 60%
Z = $2,000,000
A = $15,000
B = 40%
C = $20,000
ALPHA:
X = $1,500,000
Y = 60%
Z = $2,000,000
A = $5,000
B = 40%
C = $20,000
ZETA Score = 60% volume bias * ($500,000 30D ZETA volume / $2,000,000 total StableSwap volume) + 40% capital bias * ($15,000 ZETA external emissions / $20,000 total StableSwap external incentives) = 45%
ALPHA Score = 60% * ($1,500,000 / $2,000,000) + 40% * ($5,000 / $20,000) = 55%
T = 5,145 SHD
S = 1 (Total Scores Across Category)
As a result of this set-up, 2,165 SHD (45% of StableSwap category incentives) will go to ZETA.
As a result of this set-up, 2,614 SHD (55% of StableSwap category incentives) will go to ALPHA.
In this example, ZETA is bringing 75% of all external incentives to the StableSwap category but is only achieving 25% of the StableSwap category volume. As opposed to purely examining category volume this model instead chooses to recognize the significance of the expenditure by still having 45% of emissions go to ZETA.
Shade Protocol governance will be able to continuously modify the Volume Bias vs Capital Bias gauges in terms of its ability to express what it prioritizes and values.
Game Theory
The biggest advantages of this model is it openly incentives protocols to bring as much emissions AND volume at the same time. ShadeSwap guarantees your capital to be recognized as an external project as something significant even if immediate volume results are not achieved. This model also fairly puts all projects in competition with each other to bring volume & incentives because it is treated on a linear basis. That is to say, your $1 of volume is just as significant as a competitors. Same with the emissions you bring.
Additionally, the competition game theory becomes similar to a veGauge model but instantiated in a controllable way where SHD governance holders never lose control over what pools qualify and what the grading criteria is. New projects get the immediate peace of mind of knowing the rules of engagement on ShadeSwap.
There is no behind close door deals. No need to pass a proposal on-chain. Start emitting, start bringing volume, and your pair is immediately part of category competition.
Now, this brings up another unique problem of DEXs whenever things become too volume focused - the potential for wash trading to try to gamify these types of systems. The way this is done is if a user owns 100% of an LP pool, they can trade assets back and fourth across their own capital creating artificial and fake volume that merely seeks to inflate stats.
Shade Protocol solves this problem via social slashing - in the event of suspected wash trading the protocol fee will increase on the underlying pool. That is to say, the % of fees that goes to the LPs will decrease and the % of fees to the protocol will increase. This process will rinse & repeat until 100% of trading fees go to Shade Protocol and 0% of the fees go to LPs. In this manner, a protocol that gambles with wash trading is putting their liquidity providers (and their own capital) in jeopardy.
Summary
- Shift emission model to category competition that any protocol can join at anytime
- Remove the need for human-to-human ShadeSwap deals
- Value both volume & external emissions from partners
- Embrace free market mechanics that doesn’t overly favor incumbents or new entrants
- Social slashing in the form of increased protocol fee and decreased LP fees on offending wash trading pools
- Empower modifiable “Volume Bias” & “Capital Bias” weights so Shade Protocol governance can express how much it values volume on pairs versus external incentives.