Concept · mechanism-design
Binary Contracts
Prediction market contracts that resolve to exactly one of two values, typically $1 (yes) or $0 (no), based on whether a specified event occurs. The binary structure eliminates ambiguity at resolution and enables direct probabilistic interpretation of prices · but it also forces continuous questions into a Pareto-distributed grid of independent order books.
Key insights
- functionSPACE analyzed 36,777 Polymarket events: when one continuous question is split into ~20 binaries, the top 3 markets capture >75% of volume regardless of event size · the bottom of the distribution is structurally untradeable "ghost markets."
- The $0.01 tick size compounds the fragmentation problem · at very low probabilities, a one-cent tick is a 50%+ relative move, creating a "rounding tax" that makes low-probability contracts structurally imprecise.
- functionSPACE V2 (Apr 2026) split events into continuous (price brackets, weather ranges) vs categorical (teams, candidates): both concentrate ~90% of volume in top 5–6 markets, but ghost markets are largely a categorical phenomenon. Continuous events distribute volume more evenly and survive the liquidity cliff at high N. Continuous events overtook categorical by count in 2026Q1 · the continuous-distribution primitive applies to a growing share of the platform.
- Kalshi's revenue formula `fee = 0.07 × C × P × (1-P)` peaks at 50% probability · economically incentivizes trading near coinflip markets, structurally more poker-rake than sportsbook (Schneider analysis of 203M trades across $41.7B volume).
- Sports comprise 82% of Kalshi's volume · despite the CFTC-regulated derivatives positioning, it functions as a sports betting platform.
- Binary payoffs create clean basis risk to truth · Jeff Park argues this precision is what differentiates prediction markets from other derivatives, making them ideal for hedging exposure to specific outcomes.
- Minsky's "vega wedge" · binary hedgers replicating exposure via vanilla options pay a structural overcharge (a structural overcharge (magnitude varies by asset; the specific ~4.8%/7-20% figures are unverified)). Prediction markets can undercut that tax in deep categories (0xturbanurban).
- The binary structure makes prediction markets the purest testing environment for investment theory · binary resolution eliminates the unobservable noise that obscures strategy quality elsewhere (gemchanger).
- LMSR's pricing function is mathematically identical to softmax · bridges quant finance and prediction market pricing.
- Leverage is hard on binaries because binary outcomes resolve instantly, skipping the intermediate prices a liquidation engine needs · this is "gap risk." dYdX's TRUMPWIN perp on election night 2024 broke under real conditions despite sophisticated safeguards (Ruzicka).
- Three current approaches to leverage on binaries: constrain leverage (1x–1.5x), engineer around gap risk (dynamic fees, circuit breakers), or ship and iterate.
- Berkeley Blockchain primer: order books translate bids/asks into probabilities. Polymarket (offshore, crypto-native, public onchain) vs Kalshi (CFTC-regulated, USD, private activity) is the canonical comparator.
- Jo Lim (Strait of Hormuz 2026): binary order-book markets hit an architectural ceiling on granular, multi-outcome risk. LMSR/CLMSR offers protocol-native liquidity and coherent pricing for events without underlying assets.
In their words
Volume follows an extreme Pareto distribution: the top 3 markets capture over 75% of trading activity regardless of event size, leaving a large fraction as untradeable ghost markets.· functionSPACE, *Binary Events*
Kalshi functions more like a poker rake than a sportsbook, charging fees via the formula fee = 0.07 × C × P × (1-P), which incentivizes trading near 50% probability.· Sam Schneider, *What's Kalshi's Revenue?*
Binary outcomes resolve instantly, skipping the intermediate prices that liquidation engines need to function.· Nick Ruzicka, *Everyone's Promising 20x Leverage on Prediction Markets*
Binary payoffs create clean basis risk to truth.· Jeff Park, *What Most People Get Wrong About Prediction Markets*
Where it matters
The binary contract is the dominant primitive of the category · every Polymarket and Kalshi market is a stack of binaries. But the architecture forces continuous questions (price, magnitude, distribution) into a fragmented grid that systematically wastes liquidity in the tails. This is exactly the gap that motivates continuous-outcome markets like Dekant. The binary structure is also what makes leverage and lending hard (gap risk) · every collateralization scheme described in the literature has to engineer around the discontinuity at resolution.
Connections
- Multi-outcome markets · direct alternative to stacked binaries
- Liquidity fragmentation · the cost of the binary primitive on continuous questions
- Gap risk · the binary structure is what creates discontinuous resolution
- Semantic tick size · the $0.01 increment reads as a percentage point of probability
- Market scoring rules / LMSR · the AMM mechanism most often paired with binaries
- Order book · Polymarket's CLOB shipped because binary AMMs failed
- Adverse selection · binaries make insider edges binary too
- Hedging · binary basis risk is what makes them clean hedging instruments
Platforms linked to this concept
- Kalshi · primary · The canonical regulated binary-contracts platform
- Polymarket · primary · The canonical binary-contracts platform
- Dekant · addresses · Dekant's distribution-markets thesis is the central critique of binary contracts
- Augur · implements · Augur is a binary-contracts platform
Related concepts
- Multi-Outcome Markets
- Liquidity Fragmentation
- Gap Risk
- Semantic Tick Size
- Market Scoring Rules
- Order Book
- Adverse Selection
- Hedging
Sources
- Binary Events V2: Does Liquidity Trade The Tails? · functionSPACE · X · Apr 27, 2026
- Polls Are Dead. Long Live Prediction Markets. · Blockchain at Berkeley · X · Apr 23, 2026
- What Most People Get Wrong About Prediction Markets · Jeff Park · X · Apr 20, 2026
- The Bane Of Binaries: What Prediction Markets Are Missing · 0xturbanurban · X · Apr 15, 2026
- Binary Events: What Happens When You Split One Market Into Twenty · functionSPACE · X · Apr 2, 2026
- The World's Biggest Risk Event Just Exposed Prediction Markets' Biggest Gap · Jo Lim · X · Mar 24, 2026
- What's Kalshi's Revenue? Analyzing All 203 Million Trades on Kalshi. · Sam Schneider · Technically.dev · Mar 12, 2026
- Your Hedge Fund's Sharpe Ratio Is a Lie. Prediction Markets Are the Only Place It Can't Hide. · gemchanger · X · Feb 25, 2026
- Everyone's Promising 20x Leverage on Prediction Markets. Here's Why It's Hard. · Nick Ruzicka · Medium · Jan 27, 2026