Kalshi and prediction markets generally are highly accurate, often outperforming traditional polls and expert forecasters. Studies show prediction markets correctly forecast outcomes 70-90% of the time when markets are liquid and well-calibrated.
Kalshi's Track Record
2020 Presidential Election
- National result: Markets correctly favored Biden (though odds were closer than final margin)
- Swing states: Predicted most state outcomes correctly, better than many polls
- Tipping point: Correctly identified Pennsylvania, Wisconsin, and Michigan as key
Federal Reserve Decisions
- Rate decisions: Kalshi odds closely match actual Fed outcomes (90%+ accuracy)
- FOMC meetings: Markets accurately price in rate cuts and hikes weeks in advance
- Better than experts: Outperform individual economist predictions
Economic Data Releases
- Jobs reports: Market consensus often closer than economist surveys
- CPI/inflation: Prediction markets aggregate all available information better than single forecasters
Why Prediction Markets Are Accurate
1. Financial Incentives
Real money creates accountability:
- Traders lose money if they're wrong
- Wishful thinking gets punished by the market
- Informed traders profit from correcting mispricing
2. Information Aggregation
Markets combine diverse information sources:
- Polls, news, insider knowledge, and expert analysis
- Wisdom of crowds: many informed traders beat single experts
- Rapid incorporation of breaking news
3. Self-Correcting Mechanism
- If odds are wrong, arbitrageurs profit by correcting them
- Continuous price discovery eliminates inefficiencies
- Unlike polls, markets update in real-time
Kalshi vs Polls: Accuracy Comparison
| Method | 2020 Presidential | 2022 Midterms | Fed Decisions |
|---|---|---|---|
| Prediction markets | High accuracy | Outperformed polls | 90%+ accurate |
| Traditional polls | Missed state margins | Overstated Dem strength | N/A |
| Expert forecasts | Mixed results | Similar to polls | Less accurate |
When Kalshi Gets It Wrong
Prediction markets aren't perfect. They fail when:
1. Low Liquidity
- Small, niche markets can be mispriced due to lack of traders
- Wide spreads make accurate pricing difficult
- Stick to high-volume markets for best accuracy
2. Herding and Bubbles
- Sometimes markets follow trends rather than fundamentals
- Emotional trading can temporarily misprice outcomes
- Brexit and Trump 2016 are examples where markets underestimated unlikely outcomes
3. Limited Historical Data
- For novel events with no precedent, markets struggle
- COVID outcomes, unprecedented policy changes, etc.
4. Manipulation Risk
- In theory, wealthy actors could manipulate small markets
- In practice, rare and unprofitable in liquid markets
Calibration: The True Test of Accuracy
A well-calibrated market means:
- 70% odds should win 70% of the time: Across many events, probabilities match outcomes
- Studies show: Prediction markets are well-calibrated compared to polls and experts
- Example: If Kalshi shows 60% odds across 100 markets, ~60 should resolve "Yes"
What Academic Research Says
Extensive studies on prediction market accuracy:
- Berg & Rietz (2003): Iowa Electronic Markets outperformed polls in presidential elections
- Wolfers & Zitzewitz (2004): Markets aggregate information more efficiently than traditional forecasting
- Arrow et al. (2008): Prediction markets are the most accurate forecasting tool for complex events
How to Use Kalshi Odds Correctly
Understand Probability
- 70% odds don't mean certainty — it still happens 3 in 10 times
- Markets show probability, not predictions
- Unlikely events (20% odds) still happen 1 in 5 times
Check Liquidity
- Trust odds more on high-volume markets (presidential elections, Fed decisions)
- Be skeptical of thinly traded niche markets
- Look at order book depth and recent trading volume
Combine with Other Data
- Use Kalshi odds as one input, not the only source
- Compare to polls, fundamentals, and expert analysis
- If Kalshi disagrees with all other sources, investigate why
Kalshi vs Polymarket Accuracy
Both platforms generally show similar accuracy:
- Arbitrage keeps them aligned: Large price differences get corrected quickly
- Polymarket often higher liquidity: May be slightly more accurate on major events
- Kalshi better on US economic data: Closer to regulated institutions and US traders
Bottom Line
Kalshi is accurate, especially on liquid markets like elections and Fed decisions. Prediction markets generally outperform polls and individual experts due to financial incentives and information aggregation.
However, no forecasting method is perfect. Use Kalshi odds as a probability estimate, not a guarantee, and focus on high-liquidity markets for the most reliable signals.