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Understanding Liquidity in Prediction Markets

What is liquidity in prediction markets? Learn why it matters, how to measure it, and which platforms offer the deepest order books in 2026.

Marc Jakob
Senior Editor — Prediction Markets · · 3 min read
✓ Fact-checked · 📅 Updated 1 May 2026 · 3 min read
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Key takeaway: Liquidity stands as the paramount consideration for participants in prediction markets. Substantial liquidity translates to compressed bid-ask spreads, rapid order execution, and market prices that genuinely reflect underlying probabilities. Polymarket dominates the sector with $1.5B+ in total traded volume; alternative venues typically deliver considerably lower liquidity levels.

Prediction market liquidity shapes the entire character of your trading engagement — spanning execution costs through position unwinding velocity. However, novice traders often prioritise market selection over liquidity assessment. This article explores why market depth and trading conditions supersede other considerations.

What is liquidity?

Within financial trading ecosystems, liquidity quantifies the ease with which an asset can be transacted without materially altering its quoted price. For prediction markets, three distinct dimensions define liquidity:

  • Depth: The quantity of contracts available at successive price tiers within the order book
  • Spread: The differential separating the highest purchase offer from the lowest sale offer
  • Volume: The aggregate number of shares traded within a specified timeframe

A venue offering 10,000 shares at 48 cents on the purchase side and 10,000 shares at 50 cents on the sale side demonstrates robust liquidity. Conversely, a market presenting merely 50 shares per side with a 10-cent differential exhibits poor liquidity characteristics.

Why liquidity matters for traders

Insufficient liquidity imposes measurable financial costs through multiple channels:

  1. Wider spreads: Transaction expenses increase both upon entry and exit
  2. Slippage: Sizeable transactions push market prices unfavourably
  3. Trapped positions: Absence of willing counterparties may prevent exit prior to settlement
  4. Price inaccuracy: Shallow markets generate quotations disconnected from genuine outcome probabilities

How to measure prediction market liquidity

Prior to executing any trade, evaluate these metrics:

  • Order book depth: PolyGram's depth visualisation tools display cumulative buy and sell interest
  • 24h volume: Elevated trading activity correlates with improved fill likelihood
  • Number of unique traders: Markets attracting 100+ distinct participants typically sustain sufficient liquidity for standard retail positions
  • Spread percentage: Target markets where the bid-ask differential remains beneath 3 cents (3%) for economical execution

Which platforms have the most liquidity?

Platform Cumulative volume Avg. spread
Polymarket$1.5B+1-3 cents
Kalshi$500M+2-5 cents
Betfair ExchangeN/A (sports-focused)1-2% on sports
Augur/Azuro$50M+5-15 cents

How market makers create liquidity

Institutional liquidity providers simultaneously post buy and sell quotations, capturing the spread whilst furnishing depth to the broader participant base. Polymarket incentivises these providers through fee reductions and MATIC token distributions. PolyGram's proprietary liquidity infrastructure synchronises with Polymarket's order flow, affording PolyGram participants equivalent market depth to those trading directly on Polymarket.

Tips for trading illiquid markets

  • Deploy limit orders exclusively — refrain from market orders in thin venues
  • Distribute substantial orders across multiple price points
  • Exercise patience: establish your desired price and await execution rather than accepting unfavourable crossing costs
  • Assess temporal dynamics — shallow markets frequently deepen as settlement approaches

Engage with the sector's most liquid prediction market venue. Start trading on PolyGram →

Marc Jakob
Senior Editor — Prediction Markets

Marc has covered prediction markets and crypto order flow since 2018. Writes for PolyGram on market structure, on-chain settlement, and regulatory developments.