AMMs are price followers. Uniswap v3 and Curve do not discover prices; they passively reflect external oracle feeds or centralized exchange rates. Their constant product formula is a liquidity distribution mechanism, not a price-setting one.
prediction-markets-and-information-theory
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Why AMMs Must Evolve Beyond Constant Function Market Makers
Constant Function Market Makers (CFMMs) are flawed for prediction markets. They are static liquidity pools, not dynamic price discovery engines. This analysis argues for AMMs that respond to information entropy and time decay, using first principles from information theory.
introduction
THE FLAWED FOUNDATION
The CFMM Illusion: Liquidity ≠Price Discovery
Constant Function Market Makers conflate liquidity provision with price discovery, creating systemic inefficiencies.
Liquidity depth is illusory. Deep pools on Arbitrum or Base create a false sense of stability. This liquidity is only accessible at the oracle price, evaporating during real volatility and causing cascading liquidations.
The result is extractable value. MEV bots exploit predictable CFMM pricing, sandwiching retail trades. Protocols like CowSwap and UniswapX use batch auctions and intents to mitigate this, proving the CFMM model is obsolete.
Evidence: Over 90% of DEX volume on Ethereum L2s flows through CFMMs, yet price updates lag CEXs by 500ms+, creating a persistent arbitrage gap.
key-trends
WHY AMMS MUST EVOLVE
The Core Flaw: Static Curves in a Dynamic World
Constant Function Market Makers (CFMMs) like Uniswap V2/V3 are rigid by design, creating systematic inefficiencies that extract billions in value from LPs and traders.
01
The Problem: Predictable Loss-Versus-Rebalancing (LVR)
Static pools are sitting ducks for MEV bots. Every informed arbitrage trade extracts value from passive LPs, a structural leakage estimated at $100M+ monthly.
- LPs subsidize arbitrageurs instead of earning fees.
- Impermanent Loss is a misnomer; this loss is permanent and predictable.
- Protocols like Aevo and Hyperliquid avoid AMMs for perps due to LVR.
$100M+
Monthly LVR
0%
LP Hedge
02
The Solution: Dynamic, Oracle-Integrated Curves
Incorporate external price feeds to adjust the curve's center, neutralizing arbitrage and returning value to LPs. This turns LVR into LP profit.
- Chronos and Maverick use oracles for dynamic fee tiers and pool weights.
- Curve V2's internal oracle re-pegs its stableswap curve.
- Shifts risk from predictable arbitrage to oracle reliability, a more manageable attack vector.
~90%
LVR Recaptured
1-5s
Oracle Latency
03
The Problem: Capital Inefficiency & Fragmentation
Static concentrated liquidity (Uniswap V3) requires active management, fragmenting TVL into narrow bands. Over $1B in Uni V3 positions are currently out-of-range and earning zero fees.
- Idle capital in wide pools or out-of-range positions.
- LP attention as a scarce resource leads to suboptimal allocation.
- Creates windows of illiquidity exploitable by large trades.
$1B+
Idle Capital
0% Fee
Out-of-Range
04
The Solution: Autonomous Liquidity Management
Let the pool manage itself. Use algorithms to automatically concentrate liquidity around the market price, maximizing fee yield and reducing gas for LPs.
- Maverick's Automated Liquidity Placement (ALP) dynamically shifts bins.
- Gamma's vaults automate Uniswap V3 management.
- Moves from active LPing to a passive, yield-bearing vault model, similar to Lido for liquidity.
2-5x
Capital Efficiency
-95%
LP Gas Cost
05
The Problem: Inefficient Price Discovery for Tail Assets
Static curves for low-liquidity tokens create extreme slippage and are vulnerable to manipulation. A single large deposit can dominate the pool's price.
- Slippage often exceeds 10% for small-cap swaps.
- Easy to manipulate for oracle attacks or predatory trading.
- Deters legitimate project listing and trading.
>10%
Typical Slippage
Low
Attack Cost
06
The Solution: Hybrid Pools & Just-in-Time Liquidity
Combine on-chain curve with off-chain solvers or RFQ systems for large/tail trades. Use the AMM as a fallback, not the primary venue.
- CowSwap and UniswapX use solver networks for optimal routing.
- 1inch Fusion and Across use fillers with on-chain settlement.
- The AMM evolves into a liquidity backstop, while intent-based systems handle execution.
<0.1%
Solver Slippage
JIT
Liquidity Mode
deep-dive
THE DATA DEFICIT
First Principles: Information Theory Meets Market Design
Constant Function Market Makers are informationally inefficient, leaking value to arbitrageurs and failing to capture latent demand.
CFMMs are data-blind. They price assets using a static bonding curve, ignoring all external market signals. This creates a persistent information asymmetry where off-chain liquidity (e.g., Binance, Coinbase) dictates on-chain price discovery.
Arbitrage is a tax. The predictable slippage of a constant product formula is a direct subsidy to MEV bots. Every rebalancing trade transfers value from LPs to searchers, representing a structural inefficiency.
Latent demand is wasted. A CFMM cannot express conditional logic like "buy if below $X" or "execute across chains". Protocols like UniswapX and CowSwap demonstrate that capturing this intent off-chain is more efficient.
Evidence: Over 90% of DEX volume on Ethereum is arbitrage. This is not organic trading but a systemic leakage proving the model's informational poverty.
WHY CFMMS FAIL FOR LONG-TAIL ASSETS
AMM Archetypes: A Prediction Market Fitness Matrix
Evaluating AMM designs against core requirements for efficient, low-liquidity prediction markets.
| Core Requirement | Constant Function (Uniswap v2) | Proactive Market Maker (PM) | Virtual AMM (vAMM / Perpetual Protocol) |
|---|---|---|---|
Capital Efficiency for Long-Tail Pairs | 0.3% fee on $10k TVL = $30/day |
| Infinite (0 capital locked) |
Impermanent Loss Risk for LPs | High (Uncorrelated assets) | None (No LPs in order book) | None (Synthetic vAMM liquidity) |
Price Discovery Latency |
| < 1 block (On-chain order book) | Instant (Oracle price feed) |
Slippage for Large Orders |
| < 0.1% (Deep order book) | 0% (Oracle-based execution) |
Support for Binary Outcomes | |||
Gas Cost per Trade (Approx.) | 150k-200k gas | 250k-300k gas | 120k-150k gas |
Requires External Oracle | |||
Time-Based Settlement Native |
protocol-spotlight
THE AMM EVOLUTION
Building the Next Generation: Who's Getting It Right?
Constant Function Market Makers are a bottleneck. The next wave of DEXs is solving for price execution, capital efficiency, and user intent.
01
Uniswap V4: The Modular Hook Factory
Replaces a monolithic contract with a permissionless hook system, enabling custom AMM logic per pool. This is the infrastructure for the next decade of on-chain finance.
- Dynamic Fees: Adjust based on volatility or time of day.
- TWAMM Orders: Break large trades into smaller executions over time.
- Custom Oracles: Move beyond the native price feed for exotic assets.
~90%
Gas Saved
∞
Pool Types
02
The Problem: LPs Are Stuck Earning Spread on Stale Prices
CFMMs force liquidity providers to passively wait for arbitrageurs to correct prices, earning only the spread. This is capital-inefficient and exposes LPs to maximal extractable value (MEV).
- Inefficient Capital: >90% of an LP's capital sits idle, not earning fees.
- Loss-Versus-Rebalancing: The dominant source of impermanent loss, a direct transfer to arbitrage bots.
- Passive Role: LPs cannot actively manage positions or set limit orders.
$10B+
Idle Capital
>50%
LP Returns Lost
03
The Solution: Proactive Liquidity & Intent-Based Routing
New architectures like UniswapX, CowSwap, and Across separate order flow from execution, letting solvers compete for best price. This moves liquidity from passive pools to proactive networks.
- Intent-Based: Users express a desired outcome (e.g., "swap X for Y at >= price Z").
- Solver Competition: A network of solvers (like in CowSwap) or fillers (like in UniswapX) compete to fulfill the intent, sourcing liquidity from any venue.
- MEV Protection: Batch auctions and privacy hide transaction flow, preventing frontrunning.
20-30%
Better Price
~0
Slippage
04
Trader Joe v2.1: The Concentrated Liquidity Pioneer
Proved that concentrated liquidity (CL) AMMs with active management are viable. Their Liquidity Book model allows LPs to set discrete price ranges, dramatically boosting capital efficiency for stable and correlated assets.
- Fixed Bin Strategy: Liquidity is allocated to specific price "bins," not a continuous curve.
- Active Management: LPs can manually or programmatically re-concentrate positions.
- Gas Efficiency: Swap logic is optimized for the bin model, reducing gas costs for traders.
1000x
Capital Efficiency
-40%
Swap Gas
05
The Problem: DEXs Are Isolated Liquidity Silos
Each AMM pool is a standalone venue. A trade that hops across multiple pools (e.g., ETH -> USDC -> WBTC) fragments liquidity, multiplies fees, and increases slippage. This creates a terrible user experience for cross-asset swaps.
- Fragmented Liquidity: No single pool has deep liquidity for all asset pairs.
- Multi-Hop Slippage: Slippage compounds with each hop in the route.
- Router Complexity: Users rely on opaque routers to find the best path, often sub-optimal.
3-5x
Fee Stack
High
Slippage Risk
06
The Solution: Universal Liquidity Layers & Cross-Chain AMMs
Protocols like LayerZero's Stargate and Chainflip are building cross-chain native AMMs, while DEX aggregators (1inch, 0x) abstract liquidity sources. The endgame is a single liquidity layer accessible from any chain.
- Unified Pools: A single liquidity pool can serve users across multiple blockchains (e.g., Stargate).
- Aggregation Supremacy: >80% of large trades already route through aggregators, not direct AMMs.
- Native Cross-Chain Swaps: Swap ETH on Ethereum for SOL on Solana in one transaction, no bridging.
$1B+
Cross-Chain TVL
1-Click
Any Chain
counter-argument
THE INCUMBENT ADVANTAGE
The Pragmatist's Rebuttal: CFMMs Are Good Enough
Constant Function Market Makers dominate DeFi because their simplicity is a feature, not a bug, for core liquidity.
CFMMs are computationally trivial. The deterministic pricing of Uniswap V2/V3 and Curve pools requires minimal on-chain logic, which is the primary reason for their resilience and adoption. This simplicity is a defensive moat against more complex, failure-prone systems.
Liquidity fragmentation is overstated. The deep, battle-tested pools on Ethereum and Arbitrum create network effects that new AMM architectures struggle to overcome. For major assets, the liquidity flywheel of existing CFMMs is their strongest asset.
The upgrade path is incremental. Innovations like Uniswap V4 hooks and Curve v2's internal oracles demonstrate that evolution, not revolution, extends the CFMM model's lifespan. These are targeted fixes, not foundational overhauls.
Evidence: Over 60% of all DEX volume still flows through Uniswap and Curve, proving that for the majority of trades, the CFMM's predictable, on-chain execution is the optimal solution.
takeaways
WHY CFMMS ARE OBSOLETE
TL;DR for Builders and Architects
Constant Function Market Makers (CFMMs) like Uniswap v2 are a foundational but flawed primitive, creating systemic inefficiencies that modern DeFi can no longer afford.
01
The Problem of Lazy Liquidity
CFMMs passively wait for arbitrageurs to correct prices, creating a permanent loss vs. rebalancing cost dilemma for LPs.
- ~80% of LP capital is idle, not actively earning fees.
- LPs subsidize arbitrage to the tune of billions annually.
- Static bonding curves cannot adapt to volatile or trending markets.
80%
Idle Capital
$B+
Arb Subsidy
02
The Solution: Proactive AMMs (Uniswap v4, Maverick)
Dynamic liquidity placement turns LPs into active managers, concentrating capital around the current price.
- Maverick's AMM uses moving price ranges for up to 10,000x capital efficiency.
- Uniswap v4 hooks enable custom liquidity logic (e.g., TWAP-based, volatility-adjusted).
- LPs earn more fees with less capital at risk, reducing impermanent loss.
10,000x
Efficiency
Dynamic
Logic
03
The Problem of Fragmented Execution
CFMMs are isolated price islands. Swaps are atomic but lack cross-domain intelligence, missing better prices or routes on other venues.
- Users overpay due to latency races and MEV extraction.
- Liquidity is siloed, preventing natural price discovery across L1s and L2s.
High
MEV Leakage
Siloed
Liquidity
04
The Solution: Intent-Based & Cross-Chain AMMs (UniswapX, Across)
Separate order routing from settlement. Solvers compete to fulfill user intents across all liquidity sources.
- UniswapX aggregates off-chain liquidity, reducing gas costs by ~50% and mitigating MEV.
- Across uses a single-sided liquidity model with fast, bonded relayers.
- This creates a unified liquidity layer abstracted from underlying chains.
-50%
Gas Cost
Unified
Liquidity Layer
05
The Problem of Inflexible LP Terms
CFMMs offer a one-size-fits-all LP experience. You cannot set custom fee tiers, whitelist counterparties, or implement sophisticated risk management.
- LPs are exposed to toxic orderflow and just-in-time (JIT) liquidity attacks.
- No ability to create structured products or yield strategies within the pool.
Toxic
Orderflow
Rigid
Terms
06
The Solution: Programmable Pools (Uniswap v4 Hooks, Aperture)
Smart contracts that execute logic at key pool lifecycle events (e.g., before/after a swap, on position adjustment).
- Enables time-weighted fees, dynamic fees based on volatility, and JIT liquidity protection.
- LPs can build auto-compounding vaults or covered call strategies directly into their position.
- Transforms pools from dumb ledgers into programmable financial primitives.
Programmable
Logic
Protected
LPs
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