25% of Polymarket Volume Is Fake: Columbia Study Breakdown

A November 2025 Columbia University study dropped a bombshell on Polymarket: 25% of all trading volume over the past three years was artificial wash trading. At its peak, fake volume reached 60% of weekly activity. Sports markets were hit hardest at 45% wash trading, while election markets spiked to 95% during certain periods. This comprehensive analysis breaks down what the study found, how it affects traders, and what you can do to cut through the noise.

The Columbia Study Explained

In November 2025, researchers at Columbia University's Business School published a comprehensive analysis of Polymarket's blockchain data titled "Artificial Volume in Decentralized Prediction Markets." The study examined three years of on-chain trading activity to identify systematic patterns of wash trading.

Key Statistics from the Study

Timeline of Wash Trading Activity

What is Wash Trading?

Wash trading is a form of market manipulation where a trader simultaneously buys and sells the same asset, creating the appearance of market activity without genuine economic interest. On blockchain-based platforms like Polymarket, this typically involves trading between multiple wallets controlled by the same entity.

How Wash Trading Works on Polymarket

Types of Wash Trading Identified

The Columbia study categorized wash trading into several distinct patterns:

• Self-trading - Same wallet both buys and sells (using different orders)
• Ring trading - A → B → C → A circular trades between wallets
• Layered trading - Multiple wallets creating artificial orderbook depth
• Cross-market wash - Trading related YES/NO tokens to maximize volume
• Time-delayed wash - Offsetting trades hours or days apart to avoid detection

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Study Methodology

The Columbia researchers employed multiple detection methods to identify wash trading with high confidence:

Detection Techniques Used

Confidence Levels

The study assigned confidence levels to its wash trading identifications:

• High confidence (15% of volume) - Multiple detection methods flagged, clear funding links
• Medium confidence (7% of volume) - Strong indicators but some ambiguity
• Low confidence (3% of volume) - Suspicious patterns, insufficient conclusive evidence

The headline "25%" figure includes all three categories. Using only high-confidence identifications, the rate would be 15%—still a significant portion of total volume.

Market-by-Market Breakdown

Wash trading rates varied significantly across different market categories on Polymarket:

Sports Markets (45% Wash Rate)

Sports betting markets had the highest sustained wash trading rate. Key factors:

• High volume opportunity - Daily games provide constant trading opportunities
• Predictable timing - Games at set times make bot operations easier
• Less scrutiny - Sports markets attract less attention than political markets
• Liquidity rewards - Higher rewards for market makers in active markets

Election Markets (15-95% Variable)

Political markets showed the widest variation in wash trading rates:

• 2024 Presidential - Average 18%, but spiked to 95% during primaries
• Congressional races - Lower attention led to less wash trading (12%)
• International elections - Highest organic activity (8% wash rate)
• Cabinet/appointment markets - Variable, 15-40% depending on attention

Crypto Markets (30% Average)

Cryptocurrency prediction markets showed moderate wash trading levels:

• Bitcoin price predictions - 28% wash rate
• ETF approval markets - 35% (high airdrop farming interest)
• Altcoin markets - 32% average
• DeFi event markets - 25%

News/Entertainment (15% Average)

Lower-volume news and entertainment markets had the cleanest activity:

• Award shows (Oscars, etc.) - 12% wash rate
• Tech product announcements - 18%
• Scientific discoveries - 8%
• Pop culture events - 15%

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Why Traders Wash Trade

The study identified several primary motivations for wash trading on Polymarket:

1. Airdrop Farming (Primary Driver)

The dominant motivation is speculation about Polymarket's planned POLY token airdrop. Wash traders assume trading volume will be a key eligibility criterion, similar to previous DeFi airdrops:

• Uniswap precedent - UNI airdrop rewarded liquidity providers based on volume
• dYdX precedent - Trading volume was primary criterion for token distribution
• Blur precedent - NFT trading volume drove airdrop allocations
• Expected POLY launch - Polymarket announced token plans for 2026

The potential value of a POLY airdrop could be significant—early users of similar platforms received tokens worth $10,000-$100,000+. This creates strong incentives to maximize volume metrics even at the cost of trading fees.

2. Liquidity Mining Rewards

Polymarket's liquidity rewards program pays market makers based on provided liquidity and trading activity. Some traders exploit this by:

• Placing orders on both sides of the spread
• Trading against their own orders to collect rewards
• Maintaining "active" status without genuine market making

3. Market Manipulation

While less common, some wash trading aims to manipulate market perceptions:

• False volume signals - Make markets appear more active than reality
• Artificial momentum - Create illusion of buying/selling pressure
• Liquidity mirage - Trick other traders into thinking positions are easy to exit
• Social proof - Higher volume attracts more genuine traders

4. Builder/Referral Code Farming

Polymarket's builder code program pays referral fees based on trading volume. Some participants:

• Create wallets using their own referral codes
• Wash trade to generate referral commissions
• Extract value directly through the referral program

How This Affects Your Trading

Volume Signals Are Unreliable

If you've been using volume as a signal for market conviction or smart money activity, this study shows you need to recalibrate completely:

Whale Tracking Becomes Essential

When aggregate volume is unreliable, tracking specific whale wallets with verified track records becomes essential. Focus on:

• Verified profitable wallets - Consistent returns over time
• Organic funding sources - Not linked to wash trading clusters
• Directional conviction - Clear positions rather than offsetting trades
• Long-term holders - Not just volume churning

Tools like PolyTrack help identify genuine whale activity by analyzing wallet histories, profitability, and trading patterns to filter out wash traders.

Liquidity May Be Thinner Than Expected

With 25% of volume being artificial, actual market depth is significantly shallower than displayed metrics suggest:

• Larger slippage - Orders may move price more than expected
• Exit difficulty - Large positions may be harder to close
• Volatility spikes - Real liquidity events hit harder
• Spread widening - Actual spreads may be wider than they appear

How to Identify Wash Trading

While sophisticated analysis requires blockchain analytics tools, you can spot potential wash trading through several observable signals:

Red Flags to Watch For

Tools for Detection

• Polygonscan - Trace wallet funding sources and transaction histories
• Arkham Intelligence - Entity labeling and wallet clustering
• Nansen - Smart money labels and wallet profiling
• PolyTrack - Filters for verified profitable wallets

Technical Detection Methods

For more sophisticated analysis, these are the technical approaches used by researchers and analytics firms:

Graph Analysis

Building transaction graphs reveals wallet clusters that primarily trade with each other:

• Node analysis - Each wallet is a node in the graph
• Edge weighting - Edges weighted by trade volume between wallets
• Community detection - Algorithms identify isolated trading clusters
• Centrality metrics - Find wallets that connect wash trading rings

Statistical Analysis

• Trade timing distribution - Legitimate trading follows patterns; wash trading is often uniform
• Order size clustering - Wash trades often use round numbers or identical sizes
• Price impact analysis - Real trades move prices; wash trades often don't
• Profitability analysis - Wash traders show near-zero net P&L over time

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Polymarket's Response

Polymarket has addressed the Columbia study findings, though critics argue the response is insufficient:

Official Position

• Volume as one metric - They emphasize that volume is "one of many" indicators of market health
• Blockchain transparency - Anyone can verify activity on-chain
• Price accuracy matters most - Market prices, not volume, determine prediction accuracy
• Future token criteria - May use "more sophisticated criteria than raw volume"

Actions Taken

To date, Polymarket has:

• Not banned identified wash trading wallets
• Not removed wash trading volume from official metrics
• Not implemented wash trading detection in their UI
• Acknowledged the study without disputing its methodology

Criticism of Response

Market observers have raised several concerns:

• Misleading metrics - Retail traders may be deceived by inflated volume
• Competitive positioning - Volume claims in marketing may be misleading
• Airdrop fairness - Legitimate users may receive smaller allocations than farmers
• Regulatory risk - SEC/CFTC may view lack of action unfavorably

Implications for Accuracy Claims

Polymarket has marketed itself as "the most accurate prediction market mankind has ever seen." The wash trading findings raise questions about this claim:

The Accuracy Question

• Volume ≠ accuracy - Wash trading inflates volume but may not affect prices
• Price discovery - Genuine trades still set prices even with fake volume
• Wisdom of crowds - Effect diluted if fewer unique participants than claimed
• Liquidity mirage - Markets may seem more efficient than they are

Comparative Accuracy Data

A separate Vanderbilt University study analyzed prediction market accuracy:

While correlation doesn't prove causation, the regulated platforms with lower wash trading showed higher prediction accuracy. For platform comparisons, see our guides on Polymarket vs Kalshi and Polymarket vs PredictIt.

Regulatory Outlook

The wash trading revelations have implications for Polymarket's regulatory future:

Current Regulatory Status

Polymarket operates internationally after a 2022 CFTC settlement blocked US users. See our guide on is Polymarket legal for full details.

Potential Regulatory Concerns

• Market manipulation rules - Wash trading is prohibited on regulated exchanges
• Disclosure requirements - Inflated metrics could be seen as misleading
• Anti-money laundering - Wash trading can obscure transaction origins
• Consumer protection - Retail traders may be harmed by misleading volume

Future Regulatory Scenarios

How to Protect Yourself

Given the wash trading findings, here's how to adapt your Polymarket strategy:

Do's

• Track specific whales - Use PolyTrack to follow verified profitable wallets
• Focus on price movements - Prices are harder to manipulate than volume
• Verify wallet legitimacy - Check funding sources before following any trader
• Discount volume by 25-45% - Mentally adjust all volume figures
• Use multiple signals - Never rely on volume alone for decisions
• Be skeptical of "hot" markets - High volume could mean high wash trading

Don'ts

• Don't trust raw volume - A "$10M volume" market may have $5M real activity
• Don't assume liquidity - Exit may be harder than entry
• Don't follow "high activity" signals - Activity could be artificial
• Don't ignore sports market skepticism - 45% wash rate is significant

Adapt Your Strategy

For more detailed trading approaches, see our guides on whale trading strategies and best traders to follow.

Future Outlook

For the POLY Token Airdrop

If Polymarket uses volume as an airdrop criterion, they'll face difficult choices:

• Raw volume - Rewards wash traders disproportionately
• Filtered volume - Requires sophisticated detection
• Alternative metrics - Unique markets traded, positions held, profitability
• Hybrid approach - Multiple factors weighted together

Legitimate traders who participated organically may actually benefit if Polymarket filters wash trading activity before airdrop allocation.

For Platform Development

The study may push Polymarket to:

• Implement on-platform wash trading detection
• Display "verified volume" alongside raw metrics
• Adjust liquidity rewards to disincentivize wash trading
• Partner with analytics firms for wallet verification

For the Prediction Market Industry

The Columbia study highlights a broader challenge for decentralized markets:

• Transparency double-edged - Open data enables both verification and gaming
• Incentive alignment - Airdrops can distort genuine market activity
• Regulated vs unregulated - Regulated platforms may have cleaner data

Frequently Asked Questions