In this video, I explore LeoStrategy's choice of Rate Policy vs. Mint/Burn for Tokenized Tesla (TTSLA).
TTSLA operated on a rate policy model as opposed to what many other synthetic assets use which is a mint/burn model. The mint/burn model is being successfully used for synthetics like WBTC and was unsuccessfully used for synthetics like UST (Terra Luna).
LeoStrategy has built something beautiful in my opinion when it comes to the design of TTSLA.
Tokenized TSLA (TTSLA) uses a rate policy governance model to drive the 1:100 correlation to TSLA.
By having a liquidation preference at 1:100 and then a rate policy that dynamically adjusts to drive demand when the peg is weakening and loosen yield when the peg is strengthening, TTSLA is able to achieve TSLA-long-term exposure without sacrificing LeoStrategy's core mission of using LEO as the sole pristine collateral on their balance sheet.
LeoStrategy over-collateralizes TTSLA using LEO on their balance sheet. Then they use an autonomous, transparent and fully onchain rate policy model to either strengthen demand or loosen demand as needed to maintain the TTSLA peg.
When you combine this with the design choice of daily yield, you get something very interesting: TTSLA is able to adjust the yield every week in a programmatic way. This weekly yield policy is understood and predicted by the market because everyone knows what the next rate policy meeting will dictate (since you can just measure the price and check the table of rate policy figures to see exactly what's going to happen - or use the TTSLA Manager onchain Threads AI Agent that will tell you the current policy + the upcoming policy changes).
The predictability of this rate policy also creates stability around the peg. Since the yield is paid daily and the yield % is adjusted weekly in a way that everyone knows and can predict, market participants will arbitrage and front-run the policy changes.
This will lead to the peg becoming a self-fulfilling prophecy: everyone knows what the future rate will be. Everyone trades around the future rate. The rate increases if demand is cooling. The very increase in rate drives more buying pressure. It also drives speculative buying pressure on the idea of increased buying pressure alone.
The model is highly reflexive and one of the most interesting tokenomic designs I've ever seen. Listen to the video and let me know your thoughts below.