A proposal to renew Gauntlet’s engagement with Sushi on dynamic incentive optimization to drive efficiency and growth.
Over the past year, Gauntlet worked with the Sushi team to optimize incentive allocation across pools based on trading volume elasticity. We deployed an optimization engine that ingested on-chain and off-chain data, modeled elasticity, and generated recommendations.
Sushi implemented 612 recommendations across multiple pools. As a result of these recommendations along with an overall reduction in incentive spending and market dynamics, Sushi’s ROI increased from 10% ($0.10 earned for every dollar spent) to 133% ($1.33 earned for every dollar spent) and projected annual revenue increased by $18.3M. Click here for further reading.
Gauntlet has begun scoping the next phase of work with the Sushi team tailored to the team’s goals and to serve them more holistically:
Focused emissions are important to improve the profitability of the DAO. We will continue to work to provide an ecosystem that is funding innovation & growth while also profitable to our stakeholders. - pocketsquare
- [New] Optimizing Sushi’s overall incentive budget in order to maximize profitability while Sushi ships new products
- [New] Expanding optimization efforts across additional chains - Gauntlet’s work to date has been targeted to the Ethereum mainnet
- Continuing to optimize incentive allocation across pools as this continues to be Sushi’s largest expense
In the following sections, we will outline the case and goals for incentive optimization. The target metric is “Protocol Utility”:
Where revenue is defined as fees captured by protocol stakeholders for rewards eligible pools optimized by Gauntlet (equivalent to 5 bps * volume for typical pools) and where incentives is defined as the USD value of liquidity rewards given to LPs (varies pool-by-pool).
- Ingest additional Sushi DEX data (new chains and pools) into the platform, maintain existing data
- Develop and customize incentive optimization elasticity models
- Continuously refit, update assumptions, and analyze model outputs
- Provide weekly incentive recommendations to the Sushi team
As an example, to better understand trading dynamics and volume elasticities within Sushi, we use a combination of simulation, address tagging, and price analysis to classify arbitrage trading to separate retail volume from volume originating from bots:
Here is another view showing slippage incurred per swap for a few major Sushi pools. Positive slippage implies that the trader received more money out than they put in, which is likely arbitrage:
- Incentive and Total Budget Optimization Updates
- Coverage of Sushi’s native pools (current and future, multi-chain)
- Supported Parameters: incentive budget, allocation points per pool
- Ad-hoc analyses to understand tradeoffs between growth and profitability
- Gauntlet will share methodology details with the Sushi team along with weekly incentive recommendations
- Gauntlet will perform a quarterly retrospective on the market and results to be shared in the forum
- Out of Scope
- Protocol development work, (e.g. solidity changes that improve risk/reward)
- Formalized mechanism design outside of the supported parameters
- Risk management for Sushi’s lending protocol
As part of this engagement, Gauntlet will build a dashboard (example below) to provide key insights into incentive optimization, with the key metric being Protocol Utility.
Gauntlet charges a service fee that seeks to be commensurate with the value we add to protocols and provides a strong signal of our alignment with the protocol itself.
In order to increase our alignment with Sushi’s goal to maximize profitability, renewal pricing for the upcoming 12-month term will be structured as follows:
- Flat service fee of $500k - denominated in $SUSHI at 30d VWAP, Sablier stream at outset of the engagement, with a 12-month linear vesting period, reduced by 50% from previous year’s engagement
- Variable quarterly performance fee at 3.6% of Protocol Utility - denominated in $USDC or $SUSHI at previous day close, with no vesting period
Gauntlet will request payment at the end of every quarter for the 1-year term. Any change to the key metric requires a performance fees assessment and change, which will be put up for discussion and vote.
Quarterly Protocol Revenue: $5.5M
Quarterly Protocol Incentives: $3.8M
Quarterly Protocol Utility: $1.7M
Quarterly Gauntlet Performance Fee (3.6%): $61.2k
Gauntlet is a simulation platform for market risk management and incentive optimization. Our prior work includes optimization work for Compound, Aave, ApeSwap, Benqi, Acala, MakerDAO, and Synthetix.
- Yes, renew Gauntlet’s expanded incentive optimization engagement for 12 months
- No, do not renew