Jonas Gebele

Ph.D. Candidate @TU_Muenchen | researching blockchain-based prediction markets | exiled from @Polymarket, protected by @bundeskanzler, migrated to @Kalshi

[Jonas Gebele @j9ebele]

@miniapeur @RefineInk

[Jonas Gebele @j9ebele]

@gemchange_ltd @Polymarket @PolymarketTrade This is much more complicated... Both odds should be more or less 99.9%. Jesus Christ market is at 96% cause of the cost-of-capital of the No position. Benin also has the cost-of-capital, but since its a neg-risk market, the discount spreads across multiple books.

[Jonas Gebele @j9ebele]

If prediction markets are to scale as a global information layer, they require machine-verifiable representations of events, not just more liquidity.

Paper incl. prompts: https://t.co/oiU6s2nfEL
Dataset coming soon.

[Jonas Gebele @j9ebele]

📄New prediction market paper.

Prediction markets are meant to aggregate information into prices. But today’s ecosystem is fragmented across platforms, and prices often diverge.

Our paper explains why this happens and how large the problem really is ⤵️
https://t.co/oiU6s2mHPd

[Jonas Gebele @j9ebele]

Bottom line:

Prediction market prices do not diverge because traders are irrational or liquidity is low. They diverge because event identity is not enforceable across platforms.

Prices currently aggregate information locally, not globally.