Yield Magnetism and System Elasticity: How to Rationally View Ethena × Pendle's YT Arbitrage

Author: TEDAO

Introduction:

As the popularity of Ethena rises, a congested arbitrage chain is operating at high speed: collateralizing (e/s) USDe to borrow stablecoins on Aave, purchasing Pendle's YT/PT for returns, and then using part of the position to supply PT back to Aave for leveraged cycling, thus aiming for Ethena points and other external incentives. The results are evident, with the collateral exposure of PT on Aave sharply increasing, and the utilization rate of mainstream stablecoins being pushed to over 80%, making the entire system more sensitive to any fluctuations.

This article will delve into the operation of this capital chain, the exit mechanism, and the risk control design of Aave and Ethena. However, understanding the mechanism is just the first step; true mastery lies in analyzing the upgrades of the framework. We often habitually use data analysis tools (such as Dune) to review the "past," while what is lacking is precisely how to see the various possibilities of the "future" and truly achieve — first delineate the risk boundaries, then discuss the returns.

How arbitrage works: from the "yield side" to the "system side"

Let's first take a look at this arbitrage path: deposit eUSDe or sUSDe (sUSDe is eUSDe after staking, with native yield) in Aave, borrow stablecoins, and then buy YT/PT in Pendle. YT corresponds to future yields, while PT can always be bought at a discount because it has stripped away the yields, and it can be held until maturity to redeem at a 1:1 ratio, earning the price difference. Of course, the real "big benefit" comes from external incentives like Ethena points.

The PT obtained this way can be used as collateral on Aave, making it the perfect starting point for a circular loan: "Collateralize PT → Borrow stablecoins → Buy PT/YT → Re-collateralize." The aim is to leverage relatively certain returns to seek high-elasticity rewards like Ethena points.

How has this funding chain rewritten the lending market?

The exposure and second-order effects of Aave: Assets supported by USDe are gradually becoming mainstream collateral for Aave, with a share that once rose to about 43.5%, directly boosting the utilization rates of mainstream stablecoins USDT/USDC.

The congestion on the borrowing side: After introducing USDe eMode for PT collateral, the borrowing scale of USDe is about 370 million USD, of which about 220 million (≈60%) serves leveraged PT strategies, with the utilization rate soaring from about 50% to around 80%.

Concentration and Rehypothecation: The supply of USDe on Aave is highly concentrated, with the top two entities accounting for over 61%. This concentration, coupled with cyclical leverage, amplifies returns but also exacerbates the system's fragility.

The rule here is simple: the more attractive the returns, the more crowded the cycle, and the entire system becomes more sensitive. Any slight fluctuation in price, interest rate, or liquidity will be ruthlessly amplified by this leverage chain.

Note: The core on-chain data cited in this article is primarily based on the report published by Chaos Labs on July 17, 2025, and related market observations. Due to the dynamic nature of on-chain data, readers are advised to check the latest situation through relevant data analysis platforms.

Why "exit" has become difficult: Pendle's structural constraints

So, how to exit? When reducing leverage or closing positions in the aforementioned loop, there are mainly two ways:

Market exit: Sell PT / YT before maturity to exchange for stablecoin repayment and unpledge.

Hold until maturity exit: Hold PT until maturity, redeem 1:1 for the underlying assets and repay. This route is slower, but more stable during market fluctuations.

Why will it become difficult to exit? The difficulties mainly come from two structural constraints of Pendle:

Fixed term: PT cannot be directly redeemed before expiration, it can only be sold in the secondary market. If you want to "quickly reduce leverage", you have to watch the secondary market's mood and endure the double test of depth and price fluctuations.

The "implied yield range" of AMM: Pendle's AMM is most efficient within the preset implied yield range. Once market sentiment changes and causes yield pricing to exceed this range, the AMM may "deactivate," and trades can only occur on thinner order books, leading to a sharp increase in slippage and liquidation risks. To prevent risk spillover, protocols like Aave deploy PT risk oracles: when the PT price falls to a certain floor price, the market is directly frozen. This can avoid bad debts, but it also means that you may find it difficult to sell PT in the short term, and you can only wait for the market to recover or hold until maturity.

Therefore, exiting during stable market conditions is usually not difficult, but when the market begins to reprice and liquidity becomes crowded, exiting becomes a major friction point that requires advance preparation.

Aave's "Brakes and Buffers": Making Deleveraging Orderly and Controllable

In the face of such structural friction, how do lending protocols (like Aave) implement risk control? It has a built-in "brake and buffer" mechanism:

Freezing and floor price mechanism: If the PT price reaches the oracle floor price and maintains it, the relevant market can be frozen until maturity; after maturity, PT naturally decomposes into the underlying asset, and then safely settles/unlocks, aiming to avoid liquidity misalignment overflow caused by fixed-term structures.

Internal settlement: In extreme cases, the liquidation reward is set to 0, first forming a buffer and then gradually disposing of collateral: USDe will be sold in the secondary market after liquidity is restored, while PT will be held until maturity to avoid being passively sold on the thin order book of the secondary market, thereby amplifying slippage.

Whitelist Redemption: If the lending agreement obtains the Ethena whitelist, it can bypass the secondary market and directly redeem the underlying stablecoin with USDe, reducing impact and enhancing recovery.

Boundary of supporting tools: When the liquidity of USDe is temporarily tight, Debt Swap can convert USDe-denominated debt into USDT/USDC; however, due to the constraints of E-mode configuration, migration has thresholds and steps, requiring more sufficient margin.

Ethena's "Adaptive Base": Supports Structural and Custodial Isolation

The lending agreement has a "brake," while the asset support side needs Ethena's "automatic transmission" to absorb the impact.

Regarding the status of support structure and funding rates: when the funding rate declines or turns negative, Ethena reduces hedge exposure and increases stablecoin support; in mid-May 2024, the proportion of stablecoins once reached ~76.3%, then retraced to the ~50% range, which is still higher than previous years, allowing for proactive pressure reduction during negative funding periods.

Furthermore, from the perspective of buffering capacity: in extreme LST confiscation scenarios, the net impact on the overall support for USDe is estimated to be approximately 0.304%; a reserve of 60 million USD is sufficient to absorb such shocks (accounting for only about 27% of it), thus the substantial impact on anchoring and repayment is manageable.

The custody and isolation of assets are key components: Ethena's assets are not directly stored in the exchange, but are settled off-exchange and isolated through third-party custodians (such as Copper, Ceffu). This means that even if the exchange itself encounters operational or repayment issues, these assets used as collateral remain independent and protected in ownership. Under this isolation framework, an efficient emergency process can be implemented: if the exchange is interrupted, the custodian can invalidate open positions after missing a certain number of settlement rounds, releasing collateral, and helping Ethena quickly migrate hedged positions to other exchanges, thereby significantly shortening the risk exposure window.

When the misalignment primarily comes from "implied yield re-pricing" rather than USDe support being impaired, under the protection of oracle freezes and tiered disposal, the risk of bad debts is controllable; what really needs to be focused on preventing are tail events where the support side is damaged.

What you should pay attention to: 6 risk signals

The theory is finished, what specific indicators should we look at? The following 6 signals summarized are highly correlated with the Aave × Pendle × Ethena linkage and can be used as a daily dashboard for monitoring.

USDe borrowing and utilization rate: Continuously track the total borrowing amount of USDe, the proportion of leveraged PT strategies, and the utilization rate curve. The utilization rate is consistently above ~80%, and the system sensitivity has significantly increased (from ~50% to ~80% during the reporting period).

Aave open and stablecoin second-order effects: Pay attention to the proportion of USDe-supported assets in Aave's total collateral (approximately 43.5%), and the transmission effect on the utilization rates of core stablecoins like USDT/USDC.

Concentration and Re-collateralization: Monitor the deposit ratio of the top addresses; when the concentration of the top addresses (e.g., the sum of the top two) exceeds 50-60%, be cautious of the potential liquidity shock that may arise from their coordinated actions (peak value during the reporting period >61%).

Proximity of the implied yield range: Check whether the implied yield of the target PT/YT pool is approaching the boundary of the AMM preset range; proximity to or exceeding the range indicates a decrease in matching efficiency and an increase in exit friction.

PT Risk Oracle Status: Pay attention to the distance between the PT market price and the Aave Risk Oracle minimum price threshold; approaching the threshold is a strong signal that the leverage chain needs to "decelerate in an orderly manner."

Ethena Support Status: Regularly check the reserve composition published by Ethena. The change in the proportion of stablecoins (such as dropping from ~76.3% to ~50%) reflects its adaptation strategy to funding rates and system buffer capacity.

Furthermore, you can set trigger thresholds for each signal and plan response actions in advance (for example: utilization ≥ 80% → reduce the cycle multiple).

From Observation to Boundaries: Risk and Liquidity Management

These signals ultimately serve risk control. We can solidify them into 4 clear "boundaries" and operate around the closed loop of "risk limit → trigger threshold → disposal action."

Boundary 1: Loop Multiple

The cyclical leverage increases sensitivity to price, interest rates, and liquidity while enhancing returns (especially when external incentives are layered); the higher the multiple, the smaller the margin for exit.

Limit: Set the maximum leverage multiple and minimum margin redundancy (e.g., LTV/Health Factor lower limit).

Trigger: Utilization rate ≥ 80% / Stablecoin borrowing rate rises rapidly / Proximity to range increases.

Action: Reduce multiplier, add margin, suspend new cycles; switch to "Hold until expiration" if necessary.

Boundary 2: Time Constraint (PT)

PT cannot be redeemed before maturity, and "hold until maturity" should be regarded as the standard path rather than a temporary expedient.

Limit: Set a cap on positions that rely on "selling before expiration."

Trigger: Implied yield exceeds range / Market depth plummets / Oracle floor price approaches.

Action: Adjust the proportion of cash and margin, and adjust the exit priority; set a "only reduce, not increase" freeze period if necessary.

Boundary 3: Oracle Status

The price is close to the minimum price threshold or triggers a freeze, which means that the link enters an orderly deleveraging phase.

Limit: the minimum price difference (buffer) with the oracle base price and the shortest observation window.

Trigger: Price difference ≤ preset threshold / Freeze signal triggered.

Actions: Gradually reduce positions, increase liquidation warning, execute Debt Swap / leverage reduction SOP, and enhance data polling frequency.

Boundary 4: Tool Friction

Debt Swap, eMode migration, etc. are effective during tight periods, but there are frictions such as thresholds, waiting, additional margins, and slippage.

Limit: Tool available quota/time window and maximum tolerable slippage and cost.

Trigger: Loan interest rate or waiting time exceeds threshold / Trading depth falls below lower limit.

Action: Reserve fund redundancy, switch to alternative channels (gradual liquidation/holding until maturity/whitelist redemption), and suspend strategy expansion.

Conclusion and Future Directions

Overall, the arbitrage between Ethena and Pendle has formed a transmission chain connecting Aave, Pendle, and Ethena, from "yield magnetism" to "system resilience." The circulation on the funding side has heightened sensitivity, while structural constraints on the market side have raised the exit threshold, and the protocols provide a buffer through their respective risk control designs.

In the DeFi space, the advancement of analytical capabilities is reflected in how we view and use data. We are accustomed to using data analysis tools like Dune or DeFiLlama to review the "past", such as tracking the position changes of leading addresses or the trends in protocol utilization. This is important as it helps us identify systemic vulnerabilities like high leverage and concentration. However, its limitations are also obvious: historical data presents a "static snapshot" of risks but cannot tell us how these static risks will evolve into dynamic system collapses when market storms arise.

To see through these hidden tail risks and deduce their transmission paths, it is necessary to introduce a forward-looking "stress test"—this is precisely the role of simulation models. They allow us to parameterize all the risk signals mentioned in this article (utilization, concentration, price, etc.), put them into a digital sandbox (a joint model composed of the core mechanisms of Aave, Pendle, and Ethena protocols), and repeatedly question "What if... then what?":

If the ETH price plummets by 30% while the funding rate turns negative, how long can my position hold?

How much slippage do I need to endure to exit safely?

What should be the minimum security margin?

The answers to these questions cannot be directly found from historical data, but can be predicted in advance through simulation modeling, ultimately helping you form a truly reliable execution manual. If you want to practice hands-on, you can choose the industry-standard framework cadCAD based on Python, or you can try the new generation platform HoloBit based on the cutting-edge Generative Agent-Based Modeling (GABM) technology, which offers powerful visualization and no-code features.