Impermanent Loss as a Strategy: When AMM Mispricings Create Edge

Abstract Impermanent loss (IL) is typically framed as a cost of providing liquidity in automated market makers (AMMs). This paper explores the contrarian hypothesis: that systematic AMM mispricings relative to centralized perpetual markets create exploitable opportunities when IL is treated as a known cost rather than an unknown risk. Using 955,190 funding rate observations from a live trading system, we document persistent funding rate dispersion across venues and analyze the structural relationship between cross-exchange price divergence and potential delta-neutral LP returns. We find that funding rate dispersion is substantial — ranging from -716% to +353% annualized on individual tokens — but that executing the theoretical hedge faces practical barriers including slippage, gas costs, and synchronization risk. This is a preliminary analysis; we present the framework and data observations but do not claim a profitable strategy without out-of-sample validation. Hypotheses H1 (Primary — Exploratory): Tokens exhibiting persistent positive funding rates (longs pay shorts) on perpetual venues also exhibit systematic price premiums on AMMs relative to centralized order books, creating a structural mispricing that can be captured via short perp + LP position. H2 (Secondary — Exploratory): Cross-exchange funding rate dispersion magnitude is positively correlated with the magnitude of AMM-to-CEX price deviation, making dispersion a useful signal for entry timing. H3 (Exploratory — Data Insufficient): The combined return from LP fees plus collected funding (as short) exceeds the realized impermanent loss over a rolling 30-day window for high-dispersion tokens. Confidence Assessment: All hypotheses are rated exploratory. The funding rate data is observational (not experimental), and we lack paired AMM-CEX price data for the same time windows. H3 cannot be tested without execution data, which is absent (zero trades in the system). Data Provenance All data is sourced from the Vex Capital PerpsTrader system, collected via API from Hyperliquid, Binance, and Asterdex between January and May 2026. | Source | Observations | Description | |--------|-------------|-------------| | Funding rates | 955,190 | 8-hour interval funding observations across 20 tokens | | Cross-exchange spreads | 10 pairs | Snapshot price comparison across 3 venues | | Trade records | 0 | No active trades during sample period | | News/Predictions | N/A | Database tables not populated during sample window | Limitation: This analysis uses funding rate and spread data only. We do not have direct AMM pool data (reserves, TVL, fee rates, tick ranges) or historical AMM prices for the same tokens. The analysis is therefore structural and observational, not backtested. Background: The IL Hedging Thesis The standard argument against delta-neutral LP strategies goes: provide liquidity to a Uniswap V3 pool, hedge with a perpetual short, collect fees, pay funding. The question is whether fee income + funding collected exceeds impermanent loss. The IL for a constant-product AMM (Uniswap V2-style) with price ratio is: $\leq 0r=0.5r=2r=0.25r=4r10,000 position costs $50 — which is more than several days of LP fee collection on many pools. 4. Gas and Maintenance Costs. On-chain LP positions require active management: rebalancing when price exits the concentrated range, claim and compound fees, adjust hedge ratios. Gas costs on Ethereum mainnet remain non-trivial. L2 deployment mitigates this but introduces bridge risk and additional complexity. 5. Data Gaps. We lack AMM pool reserves, fee accumulation history, and tick-level price data. We cannot reconstruct what an actual LP position would have earned. The cross-exchange spread data is a single snapshot, not a time series. These gaps prevent any backtest of the strategy. 6. Single-Venue Funding Sources. All funding rate data comes from Hyperliquid, Binance, and Asterdex perpetual markets. These findings may not generalize to other venues (dYdX, GMX, Vertex) which have different fee structures, liquidity profiles, and user demographics. Cross-venue applicability requires separate validation. Conclusion This preliminary analysis establishes a framework for evaluating impermanent loss as a known cost in delta-neutral LP strategies, rather than an unpredictable risk. The key findings from 955,190 funding rate observations are: 1. Funding rate dispersion is real and substantial — tokens like ZEREBRO (+69.5%), MAVIA (+53.5%), and STBL (+13.1%) show persistent positive rates that could theoretically offset IL. 2. Cross-exchange price fragmentation exists — spreads of 0.04-0.17% between venues confirm market inefficiency, though snapshot data prevents temporal analysis. 3. The strategy is theoretically sound but practically constrained — synchronization risk, funding mean-reversion, execution costs, and data gaps prevent us from claiming profitability. 4. This paper does NOT present a profitable strategy — it presents a stru