Why AMM Slippage is an Information Problem, Not a Trading Problem

Slippage is an information tax. It is the penalty traders pay for interacting with a liquidity pool that lacks a global price feed. The pool's price is a local, stale state, not a market-wide consensus.

Traditional exchanges centralize information. Order books aggregate global demand into a single, efficient price. AMMs fragment liquidity, forcing each pool to independently discover price through costly arbitrage.

Intent-based architectures solve this. Protocols like UniswapX and CowSwap separate order flow from execution. They broadcast intents to a network of solvers who compete to find the best price across all venues, eliminating slippage as a user-facing parameter.

Evidence: On Ethereum mainnet, MEV searchers capture over $1M daily from DEX arbitrage. This is the explicit, outsourced cost of the AMM's information problem that intent-based models internalize and minimize.

Slippage is a tax on uninformed liquidity. It quantifies the cost of a trade's information asymmetry. The marginal price of the next unit of liquidity reveals the market's true valuation, which is hidden from the trader.

AMMs are passive oracles. A constant product curve like Uniswap v3 publishes a price derived from its reserves, not from external data. This creates a predictable arbitrage surface for MEV bots, which extract value from LPs and traders.

Intent-based architectures solve this. Protocols like UniswapX and CowSwap separate order flow from execution. They broadcast intents to a competitive solver network, which sources liquidity from the best venue, internalizing slippage as profit.

Evidence: Onchain, over 90% of profitable MEV is arbitrage. This is pure information rent extracted because the AMM's price lags the CEX. Solvers in intent systems compete to minimize this gap, converting wasted slippage into better execution.

Slippage is a price signal. The difference between a trade's expected and executed price quantifies the cost of moving the market. This cost is a real-time data point on liquidity depth and latent demand.

AMMs are naive oracles. A constant product curve like Uniswap v2's x*y=k provides a price, but its sensitivity to trade size makes it a poor standalone feed. It reflects internal pool state, not external consensus.

The problem is stale information. An AMM's price diverges from global markets until arbitrage corrects it. This arbitrage latency is the oracle's update lag, creating a profitable window for MEV bots.

Evidence: Chainlink's dominance stems from solving this. It aggregates external CEX data, providing a price that is resilient to single-pool manipulation, unlike a raw Uniswap v3 TWAP.

Slippage is a price discovery failure. AMMs are passive price-takers, not active market-makers. They lack the real-time data feeds and order books that inform centralized exchanges, creating an information asymmetry between traders and the pool.

The problem is stale oracles, not math. AMM pricing curves are deterministic. The real issue is that the pool's price diverges from the global market price because its information update mechanism (e.g., arbitrage) is slow and expensive. This is a latency problem.

Intent-based solvers like UniswapX prove this. They treat the AMM as just one potential liquidity source. By searching across venues and using private order flow, they minimize slippage by solving the information aggregation problem that a single pool cannot.

Evidence: MEV arbitrage volume. Billions in value are extracted annually by bots correcting AMM mispricing. This is pure economic waste caused by the latency of public information reaching on-chain liquidity pools.