TLDR A researcher argues prediction market insider trading enforcement should be “calibrated, not maximal” Too much or too little enforcement both hurt market accuracyTLDR A researcher argues prediction market insider trading enforcement should be “calibrated, not maximal” Too much or too little enforcement both hurt market accuracy

Kalshi Tightens Insider Trading Rules After Google Engineer and Soldier Cases

2026/06/10 15:39
3 min di lettura
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TLDR

  • A researcher argues prediction market insider trading enforcement should be “calibrated, not maximal”
  • Too much or too little enforcement both hurt market accuracy, according to a new economic model
  • Kalshi now requires traders in sensitive markets to disclose their employer before placing bets
  • Kalshi made 20+ law enforcement referrals and blocked 100+ insider trades in Q1 2026
  • A Google engineer and a US soldier were both charged with insider trading on Polymarket in 2026

Prediction markets are under growing pressure to clean up insider trading, and Kalshi is taking direct action. A new academic paper is also raising questions about how far that crackdown should go.

Balbinder Singh Gill, an assistant professor of finance at the Stevens Institute of Technology, published a paper on June 2 arguing that enforcement should be measured, not absolute.

Kalshi Tightens Insider Trading Rules After Google Engineer and Soldier Cases

His economic model found that prediction market accuracy is “hump-shaped” in relation to enforcement. Too little enforcement lets insiders crowd out regular traders. Too much removes the genuine information insiders bring to the market.

Different Trades, Different Rules

Gill argues that not all insider trading is equal. Traders who researched information independently should face the least enforcement, as punishing them discourages useful information production.

Traders using leaked or classified data should face stricter enforcement. Those who can actually influence the outcome — like a political candidate betting on their own race — should face the harshest penalties.

Kalshi Acts on Insider Trading

Kalshi rolled out new rules this week in response to a report from its independent Surveillance Audit Committee, set up in February 2026.

Traders in sensitive markets — including those tied to company performance or national security — must now disclose their employer through an online form before placing a bet.

Kalshi also introduced a risk-scoring system for each market, based on factors like regulatory compliance, insider trading risk, and national security concerns.

New whistleblower tools were also launched, letting users report suspicious trading directly to the platform.

In Q1 2026, Kalshi made over 20 referrals to law enforcement, ran more than 150 investigations, and blocked over 100 potential insider trades using its screening tools.

The moves follow two high-profile cases on rival platform Polymarket. A Google engineer was charged in May with using confidential company data to profit around $1.2 million on the platform. A US soldier was charged in April with placing bets using classified knowledge of a military operation.

Last week, the DOJ and CFTC were reported to be investigating former congressman George Santos after Kalshi froze his account over suspicious trades linked to President Trump’s February State of the Union address.

Kalshi recorded $16.81 billion in monthly trading volume in May 2026, up from $14.81 billion in April. Polymarket posted $7.08 billion in May, down from $9.01 billion the prior month.

The post Kalshi Tightens Insider Trading Rules After Google Engineer and Soldier Cases appeared first on CoinCentral.

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