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NEW: Crypto and mention markets will reportedly have the highest fees

LAWMAKERS TO INTRODUCE BIPARTISAN BILL BANNING SPORTS BETS ON PREDICTION MARKETS SUCH AS POLYMARKET AND KALSHI: WSJ

LAWMAKERS TO INTRODUCE BIPARTISAN BILL BANNING SPORTS BETS ON PREDICTION MARKETS SUCH AS POLYMARKET AND KALSHI: WSJ

At some point you realize the best growth strategy is a product people can’t shut up about

Sportsbooks are house machines designed to max extract. Prediction markets are neutral infrastructure that actually protects the consumer.

Platform & Product Stability Updates (Feb 16 - Mar 2): - Improved website performance by reducing RAM/CPU usage by ~35-50% - Identifying and removing 2x more scam comments/day compared to last month - Onboarded a new support team member plus added another Discord mod (more to come) - Reduced “Tick size” trade errors by 90% - Reduced “No Matching Order Not Found (FAK)” trade errors by 50% - Faster trade UX for Magic users - Added more detections to identify users who violate our Terms of Service - Worked with RPC providers to ensure better performance and keep up with demand - Further reduced logouts issues by ~40% Outstanding/In-Progress Items: - Researching and deploying solutions to improve order execution and reduce trade failures - Continuing to add more support team members and more Discord mods - Undergoing a Discord security audit - Investigating “Not Enough Balance” trade errors - Upgrading CLOB and smart contracts (big upgrade, more to come) - Optimizing the matching engine to improve performance - Evaluating third-party firms to enhance market integrity While there may be some bumps along the way, we're generally heading in the right direction to scale up to meet significant increases in demand so we can better serve our users & builders alike.

Pam Bondi LOSES HER MIND when asked why she has not indicted any of Jeffrey Epstein’s clients. “The Dow is over 50k right now, the Nasdaq smashing records, that’s what we should be talking about!!”

6 months ago, Kalshi did $800m monthly volume across the entire exchange. today, crypto alone is on track for $1.2B monthly — now our second largest category behind sports

prediction market shares are the most underpriced collateral primitive in crypto right now. you buy YES shares on X market at X¢, that capital is locked until resolution. but tokenize that share onchain and suddenly it's composable with all of defi. borrow against it: > a lending protocol values your X¢ YES share at probability-weighted collateral, adjusting in real time as the market moves > use the borrowed stables to take positions in other markets now you're running leveraged conviction across multiple predictions with one capital base. with time decay pricing, a YES share at 70% with 48 hours to resolution is worth more than the same share at 70% with 6 months left the example that makes this click: kalshi is already exploring tokenization on solana with jupiter and DFlow imagine a lending protocol that accepts kalshi shares as collateral: > you buy YES on "us gdp growth above 2% in q2" at 60¢ > post it as collateral > borrow 40¢ on the dollar and use that to buy YES on "fed holds rates in june" at 55¢ > you now have leveraged exposure to a macro thesis across two correlated markets using one capital base prediction markets today are $10b/month in volume sitting in isolated silos and the moment those positions plug into lending, it becomes defi itself. pm shares are the most underpriced collateral primitive in crypto right now. (which is surprising) that's cleaner collateral than half the tokens people are already borrowing against. whoever builds the lending protocol that natively understands probability-weighted collateral captures the entire intersection of prediction markets and defi.

Kalshi’s policy is to always choose poor mechanism design in favor of regulatory virtue signalling. “Last traded price prior to confirmed reporting…” just makes these markets even more ambiguous. How do you define “confirmed reporting” in this context? Also, the last traded price doesn’t equate to the true price at the time, it could have been a panic buyer/seller or a fat finger.