How to Rationally View the YT Arbitrage of Ethena × Pendle

Introduction:

As the popularity of Ethena rises, a crowded arbitrage chain is operating at high speed: collateralizing (e/s) USDe to borrow stablecoins on Aave, purchasing Pendle's YT/PT for profits, and reinvesting part of the position by supplying PT back to Aave to leverage further, aiming to earn Ethena points and other external incentives. The results are evident; the collateral exposure of PT on Aave has surged dramatically, and the utilization rate of mainstream stablecoins has been 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 tend to use data analysis tools (such as Dune) to review the "past," but what is missing is how to clearly perceive 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 since it has stripped away the yields, and can be held until maturity for a 1:1 redemption, earning the price difference. Of course, the real "big gain" comes from external incentives like Ethena points.

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

How does this financial chain rewrite the lending market?

• Aave's Exposure and Second-order Effects: Assets supported by USDe have gradually become the mainstream collateral for Aave, with its share once rising to approximately 43.5%, directly boosting the utilization rate of mainstream stablecoins USDT/USDC.
• Crowding on the Borrowing Side: After introducing USDe eMode for PT collateral, the USDe borrowing scale is approximately 370 million USD, of which about 220 million (≈60%) serves leveraged PT strategies, with the utilization rate skyrocketing from approximately 50% to about 80%.
• Concentration and Rehypothecation: The supply of USDe on Aave is highly concentrated, with the top two entities accounting for over 61%. This concentration, combined with leveraged cycles, amplifies returns but also exacerbates the system's fragility.

The rule here is very simple: the more attractive the returns, the more crowded the cycle, and the entire system becomes more sensitive. Any slight fluctuation in price, interest rates, 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 released 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 information through relevant data analysis platforms.

Why "Exit" Becomes Difficult: Pendle's Structural Constraints

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

• Market Exit: Sell PT / YT before maturity, exchange for stablecoins to repay and release collateral.
• Holding until maturity exit: Hold PT until maturity, redeem the underlying assets 1:1 for repayment. This path is slower, but it is more stable during market fluctuations.

Why will it be harder to exit? The difficulty mainly comes from two structural constraints of Pendle:

• Fixed Term: PT cannot be directly redeemed before maturity, and can only be sold on the secondary market. If you want to "quickly reduce leverage," you have to pay attention to the secondary market's conditions and endure the dual challenges of depth and price fluctuations.
• The "Implied Yield Range" of AMM: Pendle's AMM operates most efficiently within the preset implied yield range. Once market sentiment shifts, causing yield pricing to exceed this range, the AMM may become "inactive," and trades can only occur on thinner order books, leading to increased slippage and liquidation risks. To prevent risk spillover, protocols like Aave deploy PT risk oracles: when the PT price drops to a certain floor price, the market is directly frozen. This can avoid bad debts, but it also means you may find it difficult to sell PT in the short term, having to wait for the market to recover or holding it until maturity.

Therefore, exiting is usually not difficult when the market is stable, but when the market begins to reprice and liquidity becomes tight, exiting becomes a major friction point that requires advance preparation of contingency plans.

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

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

• Freezing and Price Floor Mechanism: If the PT price hits the oracle's price floor and remains, the relevant market can be frozen until expiration; after expiration, PT will naturally decompose into the underlying assets, followed by safe liquidation/unwinding, 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 segmenting the disposal 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 an illiquid order book in the secondary market, thus 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 improving recovery.
• Boundaries of Supporting Tools: During periods of liquidity tension for USDe, Debt Swap can convert USDe-denominated debt into USDT/USDC; however, it is constrained by E-mode configuration, and migration has thresholds and steps that require more sufficient collateral.

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

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

• On the status of funding rates and support structure: When funding rates decline or turn negative, Ethena reduces its hedging exposure and increases support for stablecoins; in mid-May 2024, the proportion of stablecoins reached ~76.3%, then fell back to the ~50% range, which is still high compared to previous years, allowing for proactive pressure relief during periods of negative funding rates.
• Further, from the perspective of buffer capacity: In extreme LST confiscation scenarios, the estimated net impact on the overall support of USDe is about 0.304%; a reserve of $60 million is sufficient to absorb such shocks (accounting for only about 27% of it), so the substantive impact on anchoring and payment is controllable.
• Custody and Isolation of Assets are Key Components: Ethena's assets are not directly held within the exchange but are instead managed by third-party custodians (such as Copper, Ceffu) for over-the-counter settlement and asset isolation. This means that even if the exchange itself encounters operational or repayment issues, these assets serving as collateral remain independent and protected in terms of ownership. Under this isolation framework, efficient emergency processes can be implemented: if the exchange is interrupted, the custodian can nullify open positions after missing a certain number of settlement rounds, releasing collateral and helping Ethena quickly migrate hedge positions to other exchanges, thereby significantly shortening the risk exposure window.

When the misalignment mainly comes from "implied yield re-pricing" rather than the damage to USDe support, under the protection of oracle freezing and hierarchical disposal, the bad debt risk is controllable; what really needs to be focused on is the tail events where the support side is damaged.

What You Should Pay Attention To: 6 Risk Signals

The theory has been explained, what specific indicators should we look at? The following 6 signals summarized are highly correlated with the interaction of Aave × Pendle × Ethena 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 has remained consistently above ~80%, significantly increasing the system's sensitivity (reporting period from ~50% to ~80%).
• Aave Open and Stablecoin Second-Order Effects: Focus on the Proportion of USDe Supported Assets in Aave's Total Collateral (approximately 43.5%), as well as the Transmission Effect on the Utilization Rates of Core Stablecoins such as USDT/USDC
• Concentration and Re-collateralization: Monitor the deposit ratio of top addresses; when the concentration of top addresses (e.g., the sum of the top two) exceeds 50-60%, be wary of the liquidity shock that their coordinated actions may trigger (peak value during the reporting period >61%).
• Proximity of the Implied Yield Range: Check if the implied yield of the target PT/YT pool is approaching the boundary of the AMM preset range; being close 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 minimum price threshold of the Aave Risk Oracle; approaching the threshold is a strong signal that the leverage chain needs to "decelerate in an orderly manner."
• Ethena Support Status: Regularly check the reserves composition announced by Ethena. Changes in the proportion of stablecoins (such as falling from ~76.3% to ~50%) reflect its adaptation strategy to funding rates and system buffering capability.

Furthermore, you can set trigger thresholds for each signal and plan response actions in advance (e.g.: Utilization ≥ 80% → Reduce loop multiplier).

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 Multiplier

Circular leverage increases returns (when combined with external incentives) while amplifying sensitivity to price, interest rates, and liquidity; the higher the multiple, the smaller the exit margin.

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

Trigger: Utilization rate ≥ 80% / Stablecoin borrowing rates rising rapidly / Proximity to the range increasing.

Action: Reduce multiplier, supplement margin, pause new additions to the cycle; switch to "Hold until expiration" if necessary.

Boundary 2: Time Constraint (PT)

PT cannot be redeemed before maturity, and "hold to maturity" should be viewed as a regular path rather than a temporary expedient.

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

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

Action: Increase the proportion of cash and margin, adjust the exit priority; set a "decrease only, no increase" freeze period if necessary.

Boundary 3: Oracle State

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

Limit: The minimum price difference (buffer) from the oracle's base price and the shortest observation window.

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

Action: Gradual position reduction, 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 margin, and slippage.

Limit: Available tool quota/time window and maximum tolerable slippage and cost.

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

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

Conclusion and Future Directions

Overall, the arbitrage of Ethena x Pendle connects Aave, Pendle, and Ethena into a transmission chain from "yield magnetism" to "system resilience." The circulation on the funding side increases sensitivity, while the structural constraints on the market side raise 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 rates. 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 risk but cannot tell us how these static risks will evolve into dynamic system collapses when a market storm hits.

To identify these hidden tail risks and deduce their transmission paths, it is necessary to introduce forward-looking "stress tests"—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.) and place them into a digital sandbox (a joint model composed of the core mechanisms of Aave, Pendle, and Ethena protocols), repeatedly questioning "What if... happens?":

• If the ETH price plummets by 30% while the funding rate turns negative, how long can my position withstand?
• How much slippage do I need to endure to exit safely?
• What should the minimum security margin be?

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