Queue Extractable Value (QEV)

A DeFi Primitive for Long-Dated Redemptions and Low-Liquidity Collateral

Introduction to Queue Extractable Value (QEV)

QEV is a DeFi primitive designed to address liquidity challenges associated with long-dated redemptions and low-liquidity collateral within the USD.AI protocol. By introducing a market-driven mechanism for pricing and sequencing redemptions, QEV enables depositors to access liquidity more efficiently while mitigating the risks of illiquid assets and extended lockup periods. This section provides an in-depth explanation of QEV’s purpose, mechanics, and implementation within USD.AI, focusing on its role in optimizing capital efficiency for amortizing assets such as Decentralized Physical Infrastructure Network (DePIN) and AI hardware loans.

Motivation and Background

In traditional DeFi systems, liquidity is often assumed to be readily available through automated market makers (AMMs) or secondary markets. However, assets with long maturities or low liquidity—such as tokenized real-world assets (RWAs), fixed-income instruments, or DePIN collateral—present unique challenges. Rigid redemption mechanisms can lead to liquidity mismatches, forcing participants into disorderly exits via secondary markets at steep discounts, as observed in events like the USDO++ depeg. These mismatches echo historical financial crises, such as the 2023 regional banking crisis, where liquidity constraints, rather than asset quality, precipitated systemic instability.

The USD.AI protocol addresses these issues by integrating QEV as a core mechanism to dynamically price liquidity and manage redemption queues. QEV is inspired by Flashbots’ MEV-Boost (or proposer-builder separation) design. Just as Flashbots abstracted away MEV extraction from miners and validators by introducing a structured market for transaction inclusion, QEV applies the same principle to redemption sequencing in loan repayments for amortizing assets.

Instead of treating liquidity constraints as a passive problem, QEV pre-solves the issue by embedding an auction-based prioritization mechanism directly into the system at launch, integrating it seamlessly into the cash flow & loan repayment stream. A transparent and demand-driven market determines queue positioning, preventing opaque or unfair liquidity bottlenecks.

Passive stakers also benefit, as queue priority is priced into an open auction model rather than being dictated by rigid withdrawal rules. This makes liquidity access more flexible and market-efficient, while still maintaining predictable “amortization” epoch schedules.

By defining Queue Extractable Value as an expected problem to solve for, QEV aligns liquidity optimization with the native constraints of long-maturity/amortizing assets, ensuring structured, scalable and frictionless capital deployment & withdrawal.

Mechanism Design

Amortization as "block production"

QEV relies on a structured liquidity scheduling system for yield-bearing assets with predefined repayment cycles, operating in a synchronous manner similar to how blockchains process transactions at each block. Liquidity is released in scheduled increments, ensuring controlled capital flow and sustainable redemptions. This structured unlocking follows predefined amortization schedules, providing a predictable framework for liquidity distribution, ensuring:

• Predictable liquidity distribution, preventing sudden supply shocks.

• Queue-based sequencing, similar to epoch-based unlocking in PoS staking systems.

• Capital commitment enforcement, reducing speculative volatility and premature exits

Amortization is a result of various protocol mechanics to empower the borrower while protecting the lender, but there are two mechanisms that enable the situation:

1. Lumping streaming yield distributions from long-dated yields (T-bills, veCRV, etc): primarily relates to riskless yield assets like T-bills or zero-coupon loans or any naturally yield streaming asset.

2. Principal repayment (all other loans): representing the majority of “RWA” loans, these loans naturally amortize through monthly repayments. USD.AI has monthly rollovers of 30-day zero-coupon loans to mimic a “perpetual fixed income loan” but with loan amortization increasing the size of the cash-up events / size of each auction.

Synchronous blind bid auction maturity + asynchronous borrow repayments

Given the asynchronous nature of borrower/lender liquidity patterns, QEV is synchronized to every 30 days to sum all the distributions until the next auction as there is clear visibility on repayment patterns every forward 30 days:

Example of auctions given repayment visibility:

Jan 1: First auction for ($250 liquidity)

Jan 2: Borrower A repays $100 (last) +

Jan 4: Borrower C starts new loan

Jan 15: Borrower B repays $150

Feb 1: Second auction ($170 liquidity)

Feb 4: Borrower C repays $20 (first) +

Feb 15: Borrower B repays $150

The Redemption Queue as a Market

Each epoch presents a limited supply of liquidity for redemption. As demand for exits fluctuates, a natural competition for queue positioning emerges. Instead of an inefficient first-come-first-served system, QEV structures priority access based on market-driven pricing.

• Queue positions become market-based mechanism, allowing users to bid for faster redemptions.

• A secondary market for liquidity sequencing ensures fair, transparent capital allocation.

• Demand-based pricing for redemptions optimizes efficiency in amortizing asset withdrawals.

• If no one bids, the queue enters into a FIFO distribution should anyone enter redeem. If no one redeems, all proceeds are rolled over to potentially new loans or stay in T-bills (”basic redemption / reinvests”).

QEV zkAuctions: Market-Driven Liquidity Unlocks

Rather than rigid queue lockups, QEV enables structured priority bidding through epoch-based auctions.

1. Stakers enter a redemption queue, receiving amortized liquidity over time.

2. Users bid for priority access to unlock liquidity faster.

   • Bids scale queue movement proportionally, avoiding all-or-nothing distribution situations.

   • Passive stakers receive rewards through bribe redistribution.

   • All bids are done privately via zero-knowledge proofs to avoid MEV for QEV scenarios (last block bids)

3. Winning bidders move up in the queue, while non-bidders remain in amortized scheduling.

QEV-Boost & QEV-smoothening: Structured Liquidity Optimization

Queue extractable value is inspired by Flashbots' approach to Miner Extractable Value (MEV), particularly the way MEV-Boost and smoothing mechanisms optimize transaction inclusion. Just as Flashbots introduced structured auction markets for MEV extraction, QEV brings a similar structured approach to redemption sequencing in long-dated assets.

QEV-Boost vs. MEV-Boost (aka. Blind Bid Auction)

• MEV-Boost (Flashbots): Enables market-driven block building, where validators can extract MEV while optimizing inclusion fairness.

• QEV-Boost (USD.AI): Enables market-driven redemption sequencing, allowing users to bid for priority in liquidity exits.

QEV-Smoothing vs. MEV-Smoothing (aka. whale mgmt)

• MEV-Smoothing (Flashbots): Distributes extracted MEV across validators to prevent centralization and unfair advantages.

• QEV-Smoothing (USD.AI): Redistributes liquidity access based on bids to prevent whale dominance, ensuring fair allocation.

By applying the structured auction principles of MEV-Boost, QEV ensures that liquidity allocation in long-dated assets follows an open, transparent market process rather than arbitrary or rigid redemption rules.

QEV-smoothening is solve through Allocated Liquidity: the portion of available liquidity (Δ₁) distributed to depositors based on their bid strength relative to total bids.

$$\text{Allocated Liquidity} = \left( \frac{\text{Absolute Bid}}{\sum \text{Absolute Bids}} \right) \times \Delta_1$$

[NOTE] This formula may be subject to governance updates as depositor and borrower behaviors evolve. All formulas involve trade-offs between:

• Managing small vs. large depositor interests.

• Ensuring borrowers’ liquidity needs align with depositor expectations.

The smart contracts are modular and allow onchain formula swapping via droplets, ensuring governance can optimize liquidity dynamics over time.

To prevent inefficiencies, QEV-Boost introduces an optimized auction layer for queue positioning:

• Private matching: Ensures fair, efficient queue bidding execution.

  • Given the privacy, bidders can bid at anytime for the full 30 days leading up to the next auction. The only data visibility will be the # of bidding participants relative to the # of total depositors.

• Proportional Queue Movement: Adjusts positions dynamically rather than granting full priority to the highest bidder.

• Protocol yield source: The protocol earns from these “queue bribes” or auction bids, while reducing forced early exits and volatility.

Example Scenarios

The following two diagrams are illustrations of redemption queue processes with Alice, Bob and Charlie with different deposit values & different bids. Once their priority is placed, their redemption values are calculated in proportion to their priority through the smoothening formula.

What if someone doesn’t bid into their redemption request, while other participants have? If a depositor bids 0, their absolute bid is 0, meaning:

$$\frac{0}{\sum \text{Absolute Bids}} \times \Delta_1 = 0$$

Here are two different amortization scenarios with different liquidity totals ($100k vs $250k) but the same deposit values ($950k TVL):

• Example 1 (Δ = $100,000):The largest depositor (Alice) minimally participates with a very low value bid.

• Example 2 (Δ = $250,000): The largest depositor (Alice) bids the highest absolute bid.

Example 1 (Δ = $100,000)

Depositor	Total Deposit	Absolute Bid ($)	Allocated Liquidity ($)	% of Total Liquidity Won	Original bps	Relative bps
Alice	$750,000	$7	$5,660.38	5.66%	1	7.5
Bob	$50,000	$125	$9,433.96	9.43%	25	12.5
Charlie	$150,000	$1,125	$84,905.66	84.91%	75	112.5

Example 2 (Δ = $250,000)

Depositor	Total Deposit	Absolute Bid ($)	Allocated Liquidity ($)	% of Total Liquidity Won	Original bps	Relative bps
Alice	$750,000	$6,000	$234,375	93.75%	80	240
Bob	$50,000	$250	$9,765.63	3.91%	50	10
Charlie	$150,000	$150	$5,859.38	2.34%	10	6

Economic Implications

Market-Driven Queue Optimization

By transforming queue sequencing into a liquidity market, QEV unlocks new financial primitives:

• Liquidity as a tradable asset → Queue positions can be priced, exchanged and eventually tokenized

• Dynamic pricing of redemption slots → Demand-sensitive capital allocation

• Arbitrage opportunities for strategic bidders → Optimized exit strategies create new yield mechanics

Stability & Peg Enforcement

While assets that depend on QEV-adjusted is not designed to as a traditional stablecoin (backed by fully liquid assets), it prioritizes using market-based mechanisms to calibrate lower-liquidity repayment schedules into a 1:1 liquid asset with a clear path toward re-pegging based on monetizable redemption traffic (hence “synthetic dollar”).

Structured amortization schedules & queue sequencing improve liquidity stability:

• Prevents mass liquidity shocks.

• Reduces volatility in redemption pricing.

• Minimizes systemic risk from capital flight.

In addition to instant auctions, collateral guarantees and token + cash insurance fund, QEV will be the core dampener of volatility for USD.AI depegging.

Digesting data for rapid decision making

The user interface will be similar to gas costs exposed in the UI in EVM wallets, including data streams of previous performances such as “QEV gas” UI charts over time.

A simple 3-tiered module could appear as:

Buttons	Suggested BPS Range	Expected Liquidity Wait Time	Chance of Winning Liquidity	Best for
🐢 Low BPS (Slow Redemption)	0-10 bps	2-5 epochs (longest wait)	Low (~25%)	Passive long-term lenders
🦊 Mid BPS (Balanced Redemption)	10-50 bps	1-2 epochs (moderate wait)	Moderate (~60%)	Balanced risk-tolerant lenders
🦍 High BPS (Instant Redemption)	50-100+ bps	Same epoch (immediate)	High (~95%)	Whales & immediate liquidity seekers

Summary

Queue Extractable Value (QEV) represents a necessary evolution in DeFi liquidity design. It treats redemption liquidity as an auction-based resource rather than a fixed discount function, ensuring that exits are dynamically priced according to real-time liquidity availability. Instead of relying on reactive interventions, QEV enables liquidity providers to be compensated based on queue depth, automatically adjusting incentives in response to redemption demand. This prevents reflexive depegging, ensures fair pricing, and eliminates the need for unsustainable liquidity incentives. Unlike utilization-based models, which work for short-term money markets but fail for fixed-duration assets, QEV directly prices liquidity at the protocol level, making redemptions predictable, fair, and resistant to shock events.

If low-liquidity crypto assets were to scale into DeFi capital markets & form factors, they must move beyond static liquidity assumptions and adopt market-driven mechanisms that dynamically price exit liquidity under all conditions.