As it stands, we currently target a 25% burn with
lerp based on a recent community poll and executive vote. This target to burn MKR, in my opinion, is somewhat arbitrary.
Sometimes the burn is on. Sometimes it’s off.
During pullbacks, we all scramble to decide whether we should restart the burn and by how much.
Once the Surplus Buffer hits 60M, we’ll again have to debate how to increase it while still burning MKR.
The way we currently burn MKR is not efficient. The decisions we make are arbitrary, and these discussions eat away at the already limited cognitive bandwidths of our team members.
Instead of manually adjusting our burn rates, turning them on and off when we feel like it (someone calls
lerp), we can implement an automated burning strategy based on on-chain metrics and market sentiment.
- We can counter-trade market sentiment by looking at on-chain metrics, such as long and short interest.
- The best buying opportunities tend to be when short interest across the board piles up, not just on MKR, but on the entire market.
- Conversely, the worst times to buy are when the entire market is long.
- Effectively, without knowing the current price or any previous price action, we can identify:
- Pullbacks worth buying when shorts have piled up.
- Levels to stop burning when longs have piled up.
- We have access to on-chain metrics and all exchange data for both CEXs and DEXs.
- From experience, there is reliable signal in counter-trading long and short interest.
- It’s worth looking into all the data available and determine which of it is best suited for our needs.
- Vote on a target percent of the fees to be dedicated to MKR burning, and set that DAI aside.
- Currently, we voted for 25%.
- Read long and short contracts data from on-chain metrics and select exchanges.
- We can discuss and vote on which data feeds we like.
The logic I propose below is just a suggestion for how I believe we can implement a strategy to better optimize how we burn MKR:
- For DAI that is set aside towards burning:
- If long interest maxed out:
- Burn: 0% of DAI
- If long interest at 80%:
- Burn: 5% of DAI
- If long interest at 60%:
- Burn: 10% of DAI
- If long interest equals short interest:
- Burn: 20% of DAI
- If short interest at 60%:
- Burn: 30% of DAI
- If short interest at 70%:
- Burn: 50% of DAI
- If short interest at 80%:
- Burn: 70% of DAI
- If short interest maxed out:
- Burn: 100% of DAI
- If long interest maxed out:
Edit #1: We could also agree on a base burn rate to DCA at any price, maybe 5-10% of the allotment. As short interest piles up, the automation would crank the burn rate.
Also, it’s worth noting that this does not necessarily guarantee that we are burning at exact bottoms each and every time. Shorts are often right before they are wrong. Still, by cranking the burn when shorts pile up, we are increasing the likelihood that we are burning on pullbacks at lower, more optimal prices.
The biggest downside, as I see it, is that we just burn less and retain more DAI in the SB, especially during a sustained run.
Edit #2 - In response to @ElProgreso: Governance would still have the authority to revoke the burn allotment to zero if we believe we are entering exceptionally bad times and want to wait for a "bottom.” Conversely, if we think times are good, we can vote to increase how much DAI we allocate to burn by automation. The idea though is that we all suck at timing markets and that a strategy like this takes the guesswork out of it. You probably want to burn when times are bad because the price is likely depressed and you’ll never know when the “bad times” end.
The exact implementation for this should be open to discussion. Someone willing would have to build this, but I believe the time and energy spent would be worthwhile. Not only will we optimize our MKR burn, but we will also reduce unnecessary cognitive overload on governance in the future.
- There could be some linear or logarithmic interpolation for how much we burn and at what levels.
- We can vote on how much we would like to burn in general.
- We can vote on which data feeds we trust the most.
- We can run backtests on variations of this strategy and compare them against our past burn performance.
Note: The general idea for this counter-trading strategy comes courtesy of @TomDeMichele. He and his team have worked to develop a custom trading indicator. They would be more than happy to work with us to develop a strategy to counter-trade market sentiment to burn MKR.