Why Perpetual Swaps on AMMs Are Fundamentally Flawed

AMM design is for spot. The constant product formula (x*y=k) used by Uniswap V2/V3 creates a price impact for every trade, which is acceptable for simple swaps but catastrophic for perpetual futures requiring infinite liquidity at a single index price.

Liquidity providers face asymmetric risk. LPs in protocols like GMX or Synthetix act as the passive counterparty to all traders, bearing the full brunt of funding rate payments and directional market moves, which creates chronic capital inefficiency and LP attrition.

Oracle reliance introduces latency arbitrage. To mitigate AMM price drift, perp AMMs must reference an external oracle (e.g., Chainlink), creating a predictable delay that sophisticated bots exploit, as seen in the 'just-in-time' liquidity attacks on early Perpetual Protocol v1 pools.

Evidence: The total value locked (TVL) in perp AMMs remains a fraction of CEX perp volumes, and protocols consistently grapple with >90% of LPs being underwater during volatile markets, proving the model's structural mispricing of risk.

AMMs are cooperative liquidity pools. They aggregate capital from LPs who earn fees from traders. This model works for spot trading because every swap is a positive-sum transaction for the pool, generating fees.

Perpetual swaps are zero-sum games. One trader's profit is another's loss. The protocol itself, like GMX or dYdX, acts as a neutral counterparty, not a profit-seeking entity. Pooled capital is exposed to directional risk without a cooperative fee mechanism.

The conflict creates toxic LP flows. In a perp AMM like Synthetix, LPs become the de facto counterparty to all traders. Winning traders extract value directly from the pool, creating a negative-sum outcome for LPs versus the positive-sum spot model.

Evidence: LP performance divergence. Data from protocols like Perpetual Protocol v2 shows LP returns consistently underperform spot AMMs during volatile periods, as LPs subsidize trader PnL instead of collecting pure swap fees.

Flaw 1: Discrete vs. Continuous Pricing. An AMM's price is a discrete function of its reserves, updated only on trades. Perps require a continuous, oracle-driven price feed for funding rate calculations and liquidation triggers. This creates a fundamental mismatch between the on-chain execution price and the global index price, exposing LPs to oracle manipulation risks that protocols like GMX and dYdX avoid via dedicated order books.

Flaw 2: LP Risk Asymmetry. In an AMM perp pool, LPs are the perpetual counterparty to all traders. This creates toxic adverse selection: profitable traders extract value from LPs, while losing traders saddle them with bad debt. Unlike Uniswap v3 where fees offset impermanent loss, perp losses are directional and unbounded, a structural weakness that has bankrupted protocols like Mango Markets.

Flaw 3: Capital Inefficiency. AMMs lock collateral in liquidity pools. For perps, this capital sits idle against open interest instead of being dynamically allocated to margin requirements. This leads to abysmal capital efficiency versus order book models (e.g., dYdX, Hyperliquid) or intent-based solvers like UniswapX, which only commit capital at execution. The result is higher costs and lower leverage for users.

Evidence: The TVL-to-Volume Disparity. Perp-centric AMMs like Synthetix's Kwenta exhibit a TVL-to-daily-volume ratio below 1x, while order book DEXs like Apex Protocol on Berachain achieve ratios above 10x. This metric proves AMMs require excessive locked capital to generate comparable trading activity.

AMM simplicity is a trap for perps. The constant product formula's elegance for spot trades becomes a systemic risk vector for leveraged positions. It cannot natively manage funding rates or liquidation cascades, forcing these functions into vulnerable, off-chain oracles and keepers.

Composability is an illusion when the base layer is fragile. A lending protocol like Aave or Compound composable with a flawed perp AMM inherits its liquidation risk. This creates toxic fragmentation, where protocols must build isolated safety rails, defeating DeFi's core value proposition.

Order book protocols prove this. dYdX v4 and Hyperliquid demonstrate that native risk management requires dedicated infrastructure. Their throughput and capital efficiency metrics, like dYdX's ~2K TPS on Cosmos, are only possible because they abandoned the AMM model for a purpose-built core.

AMMs are passive liquidity pools designed for spot price discovery, while perpetual futures require active, high-frequency delta hedging. This fundamental mismatch forces LPs into a role they cannot manage, exposing them to unpredictable, unbounded losses from funding rate arbitrage.

Funding rate arbitrage is a zero-sum game where LPs are the designated losers. Protocols like GMX and dYdX avoid this by using order books or peer-to-pool models, isolating LPs from this toxic flow. AMM perps, like those on Uniswap v3 via Panoptic, force LPs to be the perpetual counterparty to all traders.

The LP's risk is unhedgeable and asymmetric. An LP provides liquidity across a range, but a trader's profit from funding is linear and directional. This creates a structural negative carry for LPs, a flaw proven by the capital flight from early AMM perp experiments on EVM L2s.

Evidence: The total value locked in dedicated AMM perpetual DEXs is a fraction of the liquidity in oracle-based models like GMX or Hyperliquid, demonstrating market consensus on the superior capital efficiency of non-AMM architectures for this product.