Summary
Chaos Labs strongly supports the addition of Pendle PT tokens to the Aave V3 Core instance and has collaborated extensively with @BGDLabs to design and develop a safe and manipulation-resistant oracle setup for the PT assets. This will enable Aave to provide unmatched capital efficiency while maintaining high-level security measures to prevent shortfalls. Chaos Labs has established a comprehensive methodology to best evaluate these assets and quantify optimal parameterization based on a dynamic risk oracle configuration, as extensively covered here; below we expand on the relevant adjustments based on the mathematical implementation of the dynamic linear discount oracle.
Adjusted PT Pricing Algorithm
Given the dynamic linear discount oracle’s approximative nature in modeling the logarithmic behavior of the PT token price, we apply a transformation to more accurately capture the real-time market dynamics based on the derived Aave price.
Recall that the PT market price is given by:
where t denotes the time to maturity in years. To operate our duration-based algorithm under the specified deviation threshold from the observed PTPrice_{market}, we transform the price expression linearly to determine the discountRatePerYear:
This linear transformation provides an effective approximation of the exponential market price derivation and will be directly incorporated into our quantitative modeling framework to enable adaptive updates to discountRatePerYear in response to real-time price behavior.
Max Discount Configuration
Due to the concavity inherent in the exponential pricing model of PTs, we quantify the upper bound of discountRatePerYear—denoted maxDiscountRatePerYear—based on the theoretical maximum implied APY, as constrained by the Pendle AMM mechanics. Notably, as t→0, the per-year discount rate converges to the logarithmic implied rate, given by:
Thus, we configure:
Here, maxlnImpliedRate corresponds to the implied rate when the PT price reaches its theoretical minimum within the configured Pendle AMM, occurring when PTs constitute 96% of the liquidity pool. The minimum PT price is determined by the Pendle AMM curve:
Setting maxDiscountRatePerYear below this maximum logarithmic implied rate can lead to misrepresentation of the lower bound on Aave, preventing the oracle from tracking further price decline due to configuration constraints. This could result in inaccuracies when the minimum PT price is reached within the AMM.
For instance, below we present the evolution of the transformed discountRatePerYear assuming a Pendle-configured maximum implied APY of 50%. It is thus integral that we parameterize the maxDiscountRatePerYear based on the assumption that the discountRatePerYear will increase as the asset converges to maturity.
We are looking forward to the addition of Pendle PT Assets to Aave. They provide the platform with a significant growth path into fixed-yield products and are expected to bring meaningful revenue to the Aave DAO. Chaos Labs will be providing technical and risk analysis when specific assets will be requested through the governance process.
Disclaimer
Chaos Labs has not been compensated by any third party for publishing this recommendation.
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