Where Prediction Markets Got It Wrong: Lessons from Mispredictions

Learning from Mistakes

Prediction markets aren't perfect. Analyzing where they fail helps us understand their limitations and improve our use of market probabilities.

Companies with Challenging Predictions

1. KKR (KKR)

• Brier Score: 0.230
• Hit Rate: 67%
• Markets Resolved: 3

Markets for KKR showed higher-than-average prediction error, suggesting these outcomes were harder to forecast.

2. WMB (WMB)

• Brier Score: 0.180
• Hit Rate: 67%
• Markets Resolved: 3

Markets for WMB showed higher-than-average prediction error, suggesting these outcomes were harder to forecast.

3. NDAQ (NDAQ)

• Brier Score: 0.144
• Hit Rate: 82%
• Markets Resolved: 352

Markets for NDAQ showed higher-than-average prediction error, suggesting these outcomes were harder to forecast.

4. GE (GE)

• Brier Score: 0.108
• Hit Rate: 89%
• Markets Resolved: 47

Markets for GE showed higher-than-average prediction error, suggesting these outcomes were harder to forecast.

5. ARES (ARES)

• Brier Score: 0.107
• Hit Rate: 80%
• Markets Resolved: 5

Markets for ARES showed higher-than-average prediction error, suggesting these outcomes were harder to forecast.

Common Failure Patterns

Several patterns emerge in markets that underperform:

1. Low Liquidity

Markets with minimal trading volume often show poor calibration. Without sufficient price discovery, probabilities don't reflect true information.

2. Novel Events

First-time events or unprecedented situations lack historical anchors, making prediction difficult.

3. High Volatility Companies

Companies with erratic earnings or unpredictable management tend to generate less accurate predictions.

4. Information Asymmetry

When insiders have significantly more information than market participants, predictions suffer.

Time Horizon Analysis

Predictions further from resolution tend to be less accurate:

• 2 Weeks: 0.221 Brier score
• 10 Days: 0.186 Brier score
• 1 Week: 0.158 Brier score
• 2 Days: 0.124 Brier score

Improving Your Use of Market Data

Check volume: Low-liquidity markets warrant skepticism

Consider context: Is this an unusual situation?

Look at history: How have similar markets performed?

Compare sources: Divergence between platforms may signal uncertainty

Conclusion

Understanding where prediction markets fail is as valuable as knowing where they succeed. Use this analysis to calibrate your confidence in market probabilities.

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Analysis of 2042 resolved markets. Data as of 3/8/2026.