New study on DEI in political prediction markets with
@KolemanStrumpf
Diversity, Efficiency, and Incentives in Political Prediction Markets posted at
papers.ssrn.com/sol3/papers.…
We studied every election trade made on Kalshi in 2024 and matched the traders to their politics.
Top Line: political prediction market traders are not representative of voters, and most traders are politically biased, but the market as a whole is not biased.
How? Most traders are politically biased, but they bet small. The big traders who are motivated by profit drive most of the volume and they are not politically biased.
More details:
- Traders who placed a single trade put 73% of their money on Harris.
- Kalshi's volume came from zip codes that voted just 28% for Trump, yet 60% of it went to Republican positions.
Which traders are politically biased:
- Traders who placed a single trade put 73% of their money on Harris and had the lowest returns of any group.
- The tie between a trader's home zip code and the side the trader took weakens as trading activity rises and is not distinguishable from zero among traders with more than 100 trades.
- Active traders (>100 trades) supplied 93% of the volume, and took the same positions in red and blue zip codes.
Link to full paper below