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Spread Capture

Earning the bid-ask spread through limit orders in binary contract markets

By Prediction Pilot Research · Published April 2026 · Last reviewed May 2026

What is spread capture?

Spread capture is the practice of placing limit orders on both sides of a market and earning the bid-ask spread as both fills clear. On Kalshi, a tight 2¢ spread on a 90¢-priced contract represents a 2.2% gross return per round-trip — before exchange fees of ~1.4¢ at that price. The strategy is capacity-limited (you can't scale beyond the market's native fill rate) but is the most consistent edge available in low-volatility binary contracts.

In a prediction market context: if a contract has a best bid of 85 cents and a best ask of 91 cents, a trader could post a buy limit at 86 cents and a sell limit at 90 cents. If both fill, the trader earns 4 cents per contract, minus fees.

How it works in practice

A spread capture strategy on Kalshi typically involves:

  1. Identify wide-spread markets — Look for markets where the bid-ask spread is wider than exchange fees, indicating there is room to profit by providing liquidity.
  2. Place limit orders inside the spread — Post a buy order above the current best bid and a sell order below the current best ask, tightening the spread and offering a better price to other participants.
  3. Manage inventory — If one side fills but not the other, the trader has directional exposure. Managing this inventory risk is the central challenge of market making.
  4. Repeat — Once both sides fill (or the position is closed), the process restarts.

Academic foundations

The Glosten-Milgrom model

Glosten and Milgrom (1985) developed the foundational model of why bid-ask spreads exist. In their framework, a market maker faces two types of counterparties: informed traders (who have better information about the true value) and noise traders (who trade for other reasons). The spread compensates the market maker for the losses they expect from informed traders.

Inventory risk

Ho and Stoll (1981) modeled how a dealer adjusts bid and ask prices based on their current inventory. A market maker who accumulates a large position on one side faces the risk of a price move against them. Their model shows that optimal spreads widen as inventory risk increases.

Optimal market making

Avellaneda and Stoikov (2008) developed a continuous-time model for optimal market making in a limit order book. Their framework balances the revenue from capturing spreads against the risk of adverse price moves and inventory accumulation. The optimal strategy involves skewing quotes based on current position and time horizon.

Binary contract specifics

Spread capture in prediction markets differs from equity markets in several important ways:

Key risk — adverse selection: Wide spreads often exist for a reason. They may indicate low liquidity (few participants, slow fills) or high information asymmetry (informed traders are active). A spread capture strategy in a market dominated by informed traders will systematically lose to adverse selection — the "profitable" fills will be the ones where the informed trader was on the other side.

When spread capture works

The strategy tends to be more viable in specific conditions:

Key considerations

Sources & further reading

Prediction Pilot's Spread Capture template identifies markets with wide spreads and sufficient volume for limit-order strategies.

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