Liquidity provision in prediction markets: real yield or hidden risk

Providing liquidity in prediction markets means getting paid to stand in the middle of other people's probability estimates. Traders who think events are more likely than market prices suggest buy shares. Traders who think events are less likely sell. Liquidity providers facilitate both sides, earning spreads and fees. The returns can look attractive. The risks are distinct from other DeFi liquidity pools.

What makes prediction market liquidity unique

Standard AMM pools pair two assets that both continue existing after you withdraw. ETH/USDC pools let you reclaim some ETH and some USDC regardless of price movements. Impermanent loss hurts, but both tokens remain tradable.

Prediction market pools pair outcomes where one will become worthless. Yes shares plus No shares resolve to exactly one winning side. At expiration, you hold either $1 worth of winning shares or $0 worth of losing shares.

This binary resolution fundamentally changes the LP experience.

Before resolution, liquidity providers earn fees from trading activity. Both outcomes have value. Spreads capture profit from the flow.

At resolution, one side of the pool goes to zero. If you haven't rebalanced, you hold the losing outcome alongside the winning one. Your accumulated fees better exceed your losing position.

LP mechanics in prediction markets

Two approaches to providing prediction market liquidity exist, each with distinct risk profiles.

Order book market making

On order book platforms like Polymarket, liquidity provision means active market making.

You post bids to buy at certain prices and offers to sell at higher prices. When both sides execute, you capture the spread. A bid at $0.49 and an offer at $0.51 earns $0.02 per round trip.

Active management is required. Prices move as information arrives. Stale quotes get picked off by informed traders. You must update orders continuously or use software that does it for you.

Adverse selection poses the primary risk. Traders with better information buy from you right before prices move against you. They get the good execution. You get stuck with positions that immediately lose value.

Professional market makers deploy sophisticated systems to manage these risks. Retail participants attempting to market make manually typically lose to better-equipped competitors.

AMM liquidity provision

AMM-based prediction markets let you deposit capital into automated pools.

You provide liquidity across outcome shares. The AMM algorithm handles pricing and trade execution. Fees accumulate in the pool, accruing to LP positions.

Pool composition shifts as trades occur. If many traders buy Yes shares, the pool becomes weighted toward No shares. You effectively accumulate the less popular side.

At resolution, pool composition determines payout. If you're heavily weighted toward the losing outcome, fees must compensate for principal loss.

Unlike standard AMMs where impermanent loss can reverse, prediction market resolution is permanent. There's no recovering from holding the wrong side.

The binary outcome problem

The terminal distribution in prediction markets differs from other assets.

Stocks can end up at any value. Currencies fluctuate continuously. Traditional LP positions have smooth payout profiles relative to price movements.

Prediction market outcomes are discontinuous. One share goes to $1. The other goes to $0. No middle ground exists at resolution.

This creates gamma-like exposure without explicit options pricing.

As events approach resolution, small probability changes create large position value changes. Prices accelerate toward boundaries. The outcome becomes increasingly binary even before final resolution.

Liquidity providers experience this as intensified risk near expiration. Early pool profits can disappear in hours when resolution approaches and the market strongly favors one outcome.

Timing withdrawal matters. Exiting before resolution locks in accumulated fees without final outcome risk. Staying through resolution means betting your fees exceed potential losses.

Calculating expected returns

Expected LP returns depend on multiple factors.

Fee income accumulates from trading activity. Calculate expected fees as: trading volume × fee percentage × your share of the pool.

A pool with $1 million daily volume and 0.3% fees generates $3,000 daily in fees. Your share of $100,000 in a $500,000 pool (20%) earns $600 daily, or roughly 0.6% daily return.

Spread income (for market makers) depends on realized spreads and fill rates. Quote a $0.02 spread, get filled 1,000 times daily, earn $20.

Resolution loss depends on final pool composition and outcome. If you hold 60% losing shares worth $60,000 face value, you lose $60,000 at resolution minus accumulated fees.

Break-even analysis combines these factors. How many days of fee income do you need to offset potential resolution losses? If expected resolution loss is $10,000 and daily fees are $500, you need 20 days to break even.

Probability-weighted returns incorporate outcome likelihoods. A 70% probability outcome has different expected value than a 50% probability outcome. Weight potential resolution losses by their probabilities.

Financial market implications

Prediction market liquidity provision creates exposure resembling certain derivatives positions.

Options parallels emerge. LP positions have convex payoffs near resolution, similar to short straddles. You profit when outcomes stay uncertain and lose when events resolve decisively. The analogy is imperfect but illuminating.

Novel risk profiles demand new frameworks. Standard LP analysis tools fail. Impermanent loss calculators designed for continuous price pairs don't capture binary resolution dynamics.

Hedging opportunities exist. Sophisticated participants can hedge LP positions using offsetting bets. Taking directional positions opposite to pool drift can neutralize resolution risk while maintaining fee income.

Correlation matters. If you LP across multiple prediction markets, outcomes may correlate. All your positions resolving against you simultaneously compounds losses. Diversification helps only when events are independent.

Economic implications

Prediction market liquidity provision represents a form of real yield.

Value creation underlies returns. Traders pay for the ability to express views and hedge risks. Liquidity providers earn by supplying that service. No token printing or emission schedule is required.

Sustainable economics exist. Unlike yield farms dependent on token subsidies, prediction market LP returns can continue indefinitely if trading demand persists. The fundamental service has economic value.

But risks are often underpriced. Many LPs don't fully account for resolution risk, adverse selection, or correlation effects. Apparently attractive yields may not compensate for actual risks.

Market quality affects information value. Deep liquidity improves price discovery. Shallow liquidity creates noise and manipulation opportunities. LPs who provide capital improve market function, earning compensation for that contribution.

A 5-point evaluation framework

Before providing prediction market liquidity, evaluate these dimensions:

1. Volume sustainability. Is current trading volume likely to persist? One-time event markets may spike during news cycles then go dead. Recurring markets (weekly outcomes, rolling predictions) provide steadier volume.

2. Fee adequacy. Do fees compensate for resolution risk and adverse selection? Calculate break-even scenarios. How many days of fees offset a worst-case resolution?

3. Information asymmetry. Who trades in this market? Markets dominated by informed traders pose adverse selection risk. Markets with retail speculation offer better LP economics.

4. Pool composition dynamics. How does the pool rebalance as trading occurs? Does it accumulate the less popular side? What's the worst-case composition at resolution?

5. Exit optionality. Can you withdraw before resolution if conditions change? Are there lockups? What happens to accrued fees if you exit early?

Related Concepts

• Prediction market mechanics: How markets work at the protocol level
• Prediction market fees: Who captures value from trading
• Real yield: Distinguishing sustainable returns from emissions
• Liquidity mining: Token incentives for liquidity providers