The DN DEX Quote Decay Index measures how crypto swap quotes deteriorate over 5, 15, 30 and 60 seconds. Compare quote freshness, slippage risk, routing and execution architecture across CoW Swap, Jupiter, 1inch, OKX DEX and 0x.

Data checked: 1 September 2026

Methodology version: DN-QDI v1.0

Affiliate disclosure: Some links in this research are affiliate links. Decentralised News may receive compensation when eligible readers use them. Affiliate relationships do not determine methodology, scores, inclusion or conclusions.

Summary

A DEX quote is not a permanent price. It is a snapshot or execution proposal built from liquidity, routing, gas, market prices and protocol-specific rules at a particular moment. The longer a trader waits before signing or executing, the greater the chance that the quote becomes economically stale.

The DN DEX Quote Decay Index measures that deterioration in basis points across fixed time intervals while separating market movement from deterioration attributable to routing and liquidity.

The central DN metric is:

Residual Quote Decay = Raw Quote Decay − Reference Market Move

This matters because a quote that worsens by 20 basis points while the underlying market simultaneously moves 18 basis points has behaved very differently from a quote that deteriorates 20 basis points in an unchanged market.

The Index therefore measures quote freshness, not merely slippage.

Key Findings

• Quote decay and price impact are different. Price impact exists when the quote is created because the trade itself consumes liquidity. Quote decay occurs after that quote has been observed.
• Quote decay and execution slippage are also different. A quote can deteriorate before a transaction is even submitted.
• Raw quote deterioration must be adjusted for market movement. Otherwise a benchmark can incorrectly blame a DEX for BTC, ETH or another asset simply changing price.
• A fixed “quotes expire after X seconds” rule is misleading. Different architectures use snapshot quotes, executable transactions, solver systems, RFQs, auctions and intents.
• CoW Protocol explicitly warns that quotes are snapshots and recommends obtaining a new quote when more than 30 seconds has elapsed in its integration guidance.
• 1inch Fusion cannot be evaluated like a conventional static quote. Its intent architecture uses a Dutch-auction rate that evolves through time.
• 0x explicitly distinguishes price impact from slippage, defining slippage as market movement between quotation and execution rather than the market impact created by the trade itself.
• Jupiter’s current Swap V2 preserves its order-and-execute workflow, allowing quote creation and execution timing to be measured as distinct stages.
• Quote freshness becomes more important with volatile assets, fragmented liquidity, longer signing delays and larger trade sizes.

Quick Verdict: The Wrong Question Is “Which DEX Has the Best Quote?”

The more useful question is:

Which route is still economically attractive by the time I can actually execute it?

A DEX may display the best quote at second zero and still deliver an inferior trading experience if that price deteriorates rapidly before execution.

Another route might initially quote two basis points worse but remain much more stable over the next 15 seconds.

For an actual trader, the second route may be superior.

That creates an overlooked dimension of execution quality:

Temporal Execution Quality

Traditional DEX comparisons usually measure price across venues at one moment.

The DN Quote Decay Index adds another dimension:

price through time.

What Is DEX Quote Decay?

Suppose you want to swap:

10 ETH → USDC

At 12:00:00, Aggregator A says:

Expected output: 40,000 USDC

You wait 15 seconds.

An otherwise identical fresh quote now says:

39,960 USDC

The new quote is 40 USDC worse.

Raw quote decay is:

(40,000 − 39,960) ÷ 40,000 × 10,000

= 10 basis points

For a $40,000 trade, 10 basis points represents approximately:

$40

But that still does not tell us whether Aggregator A performed poorly.

Suppose ETH itself moved against the transaction by eight basis points during those same 15 seconds.

The economically useful observation is approximately:

10 bps raw deterioration − 8 bps market deterioration

= 2 bps residual quote decay

That is a very different conclusion.

The DN Quote Decay Formula

For an exact-input trade:

Raw Quote Decay

QD(t) = 10,000 × (Q₀ − Qₜ) / Q₀

Where:

Q₀ = output amount quoted at time zero
Qₜ = fresh output quote after elapsed time t

Interpretation:

Positive value: quote became worse
0: no deterioration
Negative value: quote improved

The More Important Metric: Residual Quote Decay

Markets move.

A credible benchmark therefore needs a control.

DN defines:

Residual Quote Decay

RQD(t) = Raw Quote Decay(t) − Reference Market Deterioration(t)

Consider:

Raw DEX quote deterioration:

22 bps

Reference market deterioration:

18 bps

Residual:

4 bps

Now consider another aggregator:

Raw deterioration:

22 bps

Reference market deterioration:

2 bps

Residual:

20 bps

The headline quote changed by the same amount.

The execution-quality interpretation is completely different.

This distinction should prevent one of the largest methodological errors in DEX benchmarking.

Quote Decay Is Not the Same as Price Impact

This distinction is fundamental.

Price impact describes how much your own requested trade moves through available liquidity.

Quote decay describes what happens to an otherwise comparable quote as time passes.

Execution slippage describes the difference between expected and ultimately realised execution.

0x’s current documentation similarly distinguishes price impact from slippage and describes slippage as price movement occurring between quote generation and confirmation.

Academic work on AMM slippage has reached a related distinction. A 2026 survey separates endogenous deviation caused by the swap itself from exogenous deviation caused by activity occurring during the latency interval.

DN builds on this logic but focuses specifically on the life cycle of the quote before execution.

The DN Quote Life Cycle

A user’s swap is not one instant.

It can be represented as:

Request

↓

Route discovery

↓

Quote generated

↓

Quote displayed

↓

Human decision time

↓

Wallet interaction

↓

Signature

↓

Transaction submission

↓

Block inclusion or solver execution

↓

Final settlement

Price and liquidity can change anywhere along that path.

That means:

Execution latency begins before blockchain confirmation latency.

This is particularly important on mobile devices, hardware wallets and multi-signature wallets where several seconds can pass between the first quote and transaction submission.

DN DEX Quote Decay Benchmark

Every protocol should be tested at:

DN should record both median and tail outcomes.

A platform whose average result looks excellent can still present poor execution risk if its worst 5% of observations deteriorate dramatically.

Therefore the dataset should track:

DN Quote Half-Life

“Half-life” does not mean that a crypto price loses half its value.

DN defines Quote Half-Life as:

The time required for median adverse residual quote decay to consume 50% of the user’s specified slippage budget.

Assume:

User slippage budget:

50 bps

Half of the budget:

25 bps

If median residual quote deterioration reaches 25 bps after 42 seconds, DN Quote Half-Life is:

42 seconds

Longer is better.

A route with a 90-second Quote Half-Life is more tolerant of human or wallet delay than one with a 12-second half-life, other things being equal.

DN Requote Breach Rate

Another proprietary metric is:

Requote Breach Rate

Number of observations where residual decay exceeds the allowed budget ÷ total observations

Example:

500 observations

38 exceed a 50-basis-point budget

Requote Breach Rate:

7.6%

This tells users something an average cannot.

A venue can have:

median decay = 2 bps

while still experiencing occasional:

100+ bps quote shocks

on volatile or illiquid assets.

For trading systems, those tails can matter more than the average.

Why Raw Cross-DEX Rankings Can Be Misleading

It would be methodologically weak to place every DEX aggregator into one table and simply declare a global winner.

Jupiter operates in a predominantly Solana execution environment.

CoW, 1inch, 0x and EVM-based routing operate under different:

• block characteristics
• gas economics
• liquidity venues
• solver systems
• market-maker participation
• transaction construction
• confirmation conditions

DN should therefore create cohorts, not one misleading universal league table.

EVM Quote Decay Cohort

CoW Swap
1inch
0x / Matcha
OKX DEX
other qualifying EVM aggregators

Solana Quote Decay Cohort

Jupiter
OKX DEX where comparable
other qualifying Solana routers

Cross-chain execution deserves a separate benchmark because bridge and destination settlement latency introduce additional variables. That is why it remains Article #2 in the V11 programme rather than being mixed into this index.

How Different DEX Architectures Change Quote Decay

CoW Swap: A Quote Is Only the Beginning of the Solver Process

CoW Protocol uses signed trading intents and solver competition rather than treating the trade as a conventional AMM transaction.

Its API quote includes fields such as:

• expected amounts
• network costs
• quote ID
• order validity
• quote expiration

Its documentation explicitly describes quotes as estimates of current market conditions and warns that liquidity, gas and market conditions may change after a quote is produced. Its integration guidance recommends re-quoting if more than 30 seconds has passed.

This makes CoW particularly interesting for DN testing.

The benchmark should distinguish:

quote freshness

from:

solver execution quality

A solver architecture may ultimately deliver better execution than a simple stale-quote comparison suggests.

DN classification

Architecture: Intent / solver
Quote model: Time-sensitive estimate
Explicit expiration: Yes
Important variable: Solver competition after intent submission
Research priority: High

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1inch Fusion: Quote Decay Is Partly an Auction

1inch Fusion requires different treatment.

Its gasless intent architecture operates through a Dutch-auction mechanism.

The order rate changes through time as resolvers compete to fill the user’s intent. Current documentation describes configurable auction duration, auction start timing and price-curve behaviour.

Therefore a naïve test saying:

“The 1inch quote changed, therefore the quote decayed”

could be wrong.

Part of the evolution may be intentional auction mechanics.

For 1inch, DN should measure:

initial economic quote

versus:

minimum return

versus:

actual resolver outcome

versus:

contemporaneous reference price

This is precisely why architectural normalization matters.

DN classification

Architecture: Intent / resolver / Dutch auction
Quote model: Dynamic
Important variable: Auction curve
Raw quote-decay comparability: Limited without adjustment
Research priority: High

Jupiter: Quote-to-Execution Latency on Solana

Jupiter remains a particularly important Solana benchmark.

Its Swap V2 architecture uses an /order followed by /execute flow. Jupiter’s migration documentation states that V2 retains the previous order-and-execute interface while moving the system onto the current Swap V2 API.

The order workflow gives DN clearly identifiable timestamps:

request

→ order

→ signature

→ execute

→ settlement

That creates an excellent basis for measuring:

• quote generation latency
• wallet delay
• transaction landing
• route changes
• final execution

Jupiter’s documentation also demonstrates that an order response exposes route composition, price impact and timing information.

DN classification

Architecture: Solana meta-aggregator/router
Quote model: Transaction-ready order workflow
Important variable: Quote-to-signature-to-landing time
Research priority: Very high

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OKX DEX: Multi-Chain Routing Creates a Valuable Test Case

OKX DEX describes its routing process as comparing quotes across DEXs and professional market makers while taking price, slippage and transaction costs into account.

Its flow separates:

quote acquisition

from:

swap construction

and then:

broadcast

That creates several points at which market conditions can change.

It also makes OKX particularly useful because the same aggregation ecosystem can potentially contribute observations across several chains.

DN classification

Architecture: Multi-chain DEX aggregator
Quote model: Quote then swap construction
Important variable: Routing and transaction-construction delay
Research priority: Very high

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0x / Matcha: Indicative Price Is Not the Final Quote

0x provides another useful distinction.

Its API separates an indicative /price request from the transaction-ready /quote stage.

That difference should be preserved in DN testing.

A website displaying an indicative price is not necessarily displaying the price that should be treated as an executable commitment.

0x also explicitly distinguishes:

price impact

from:

slippage

which makes it a useful methodological reference for this Index.

DN classification

Architecture: Aggregator
Quote model: Indicative price plus executable quote
Important variable: Price-to-quote and quote-to-settlement timing
Research priority: High

The DN Quote Decay Test Protocol

For every qualifying observation DN should record:

1. UTC timestamp.
2. Network.
3. Aggregator.
4. Sell asset.
5. Buy asset.
6. Exact-input amount.
7. USD-equivalent trade size.
8. Quote output at T0.
9. Reference-market price at T0.
10. Quote response latency.
11. Route composition where available.
12. Fresh identical quote at T+5.
13. Fresh identical quote at T+15.
14. Fresh identical quote at T+30.
15. Fresh identical quote at T+60.
16. Reference-market movement at each interval.
17. Raw quote decay.
18. Residual quote decay.
19. Route changes.
20. API or quotation failures.

This should run repeatedly rather than once.

One isolated result is an anecdote.

Ten observations are interesting.

Thousands of timestamped observations begin to constitute a market-quality dataset.

Three Liquidity Buckets

DN should also avoid testing only ETH/USDC.

Tier 1: Highly Liquid

Examples:

ETH/USDC
WETH/USDT
SOL/USDC

Purpose:

baseline routing efficiency

Tier 2: Liquid Altcoins

Purpose:

Test the point where fragmentation starts becoming important.

Tier 3: Long-Tail Assets

Purpose:

Expose routing instability, liquidity fragmentation and tail deterioration.

This matters because existing empirical work has found transaction-cost characteristics to vary substantially with asset type and trade size. Research using Uniswap quote data found that larger trades become increasingly dominated by price impact and slippage, while less mature assets showed greater exposure to adverse slippage.

Four Order Sizes

Every liquidity bucket should be sampled at economically different order sizes.

For example:

$1,000

Retail baseline.

$10,000

Active trader.

$100,000

Professional/HNW execution.

$1,000,000

Institutional stress scenario where sufficiently liquid and safe to model.

This matters because DEX transaction economics are nonlinear. Recent academic research comparing centralized and decentralized markets also finds that fixed blockchain costs matter more for smaller transactions while DEX economics can become more competitive as transaction size increases.

Worked Example: Why Quote Age Can Cost More Than the Advertised Fee

Suppose a trader swaps:

$100,000

Initial route:

100,000 USDC → 24.500 ETH

Fifteen seconds later:

100,000 USDC → 24.463 ETH

The quote deteriorated by approximately:

15.1 bps

Equivalent economic difference:

approximately $151

Suppose the underlying reference market moved only:

5 bps

The approximate residual deterioration is therefore:

10.1 bps

or around:

$101

A trader comparing protocols solely on a two-basis-point advertised fee difference would miss the larger economic variable.

That is exactly the problem the DN Quote Decay Index is designed to expose.

What Causes a DEX Quote to Decay?

Several mechanisms can change a quote after it appears.

External Market Movement

BTC, ETH or the relevant token simply changes price.

This should largely disappear from the residual metric after reference adjustment.

Other Traders Consume Liquidity

The reserves or order-book liquidity supporting the original route change before execution.

Arbitrage

Searchers rebalance discrepancies across pools.

A route that existed at second zero can disappear rapidly.

Gas Conditions Change

Some routing systems include network economics in their calculation.

Solver or Market-Maker Quotes Change

RFQ and intent architectures may depend on off-chain liquidity providers whose prices continuously update.

Route Composition Changes

The best route might move from:

Pool A → Pool B

to:

Pool C → Pool D → Pool E.

The output can change even when the broad underlying asset price barely moves.

Wallet Delay

The DEX does not control how quickly the user reads, confirms or signs a transaction.

But from the user’s perspective, that delay still affects whether the displayed quote remains economically useful.

A New Metric: Human Confirmation Risk

This gives DN another unique research concept.

Most API benchmarks assume machines.

Most actual users are humans.

A human might:

1. inspect a price,
2. click Swap,
3. open a wallet,
4. inspect the wallet simulation,
5. verify the destination amount,
6. approve with biometrics or hardware wallet,
7. finally sign.

Ten or twenty seconds can pass.

Therefore DN should eventually publish:

DN Human Confirmation Risk

Expected adverse quote deterioration during a representative human confirmation interval.

This could be measured separately for:

5 seconds: fast desktop wallet

15 seconds: ordinary confirmation

30 seconds: cautious user or mobile wallet

60 seconds: hardware/multisig friction

That is a metric almost no consumer crypto publication currently treats as a first-class variable.

DN DEX Quote Decay Calculator

The proprietary tool below lets a user compare an original quote with a later fresh quote.

It calculates:

• raw quote decay
• market-adjusted residual decay
• dollar deterioration
• decay velocity
• percentage of slippage budget consumed
• DN freshness grade

The calculator does not obtain live quotes and does not recommend execution. It analyses values supplied by the user.