Ultimatum! Meta enters prediction market, monthly trading volume $14 billion. If Asian regulators ignore again, information sovereignty will be handed over!

Zuckerberg has started to get personally involved. The New York Times reports that he is leading a team to develop a prediction market app called Arena. A major tech company investing such resources indicates that this industry has moved past the experimental stage, and the business model has been validated.

Currently, the global prediction market monthly trading volume has exceeded $14 billion, with the combined valuation of major platforms totaling approximately $40 billion. Its origins can be traced back to political betting in 18th-century London coffeehouses, and later to the Iowa Electronic Markets (IEM) founded by three economists at the University of Iowa in 1988. From 1988 to 2004, the IEM outperformed traditional polls about three-quarters of the time. Today, each contract settles in a binary yes/no manner—$1 is paid if the event occurs, otherwise $0—with the trading price directly reflecting the probability. 40 cents represents a 40% probability.

The core mechanism is "skin in the game": participants who make incorrect judgments lose money, forcing them to back their opinions with real money. A study by a Federal Reserve economist in February 2026 showed that since 2022, prediction market interest rate expectations ahead of Federal Open Market Committee meetings have been highly consistent with actual outcomes, outperforming fed funds futures and the Bloomberg consensus. In the June 2026 South Korean local elections, Polymarket correctly predicted the winners in 14 of 16 major cities and provinces. When the stablecoin interest income cap issue emerged in March 2026, the prediction market immediately priced in a 97.6% probability of a decline in Coinbase's stock price, serving as a real-time risk indicator.

A 2015 study of internal prediction markets at companies such as Google and Ford found that prediction errors were reduced by up to 25% compared to official models. Of course, there are weaknesses: in the Venezuela case in January 2026, someone used confidential information for insider trading, but was identified and prosecuted, demonstrating that the market aims for transparency and accountability.

The United States has already incorporated prediction markets into the regulated financial system through judicial rulings—courts have ruled that election predictions are not games of chance, and the CFTC has no authority to ban them. This ruling has become a catalyst for traditional financial institutions like ICE, Robinhood, and CME to enter the space. However, in major Asian jurisdictions, the binary settlement structure is still equated with traditional gambling, with regulatory perspectives focused on gambling control and public order. Only India and Indonesia are exceptions.

This divergence raises three issues: First, regulatory arbitrage—users move to offshore platforms, capital flows out, and regulators lose oversight and tax revenue. Second, loss of information sovereignty—in Asian elections, prediction markets are faster and more accurate than traditional polls, but the data accumulates on foreign servers, and foreign media understand local societies better than domestic analysts. Third, lack of user protection—simply denying the market without regulating it only pushes users toward risk.

What is needed now is no longer stricter enforcement, but to initiate forward-looking discussions, bring these transactions into the formal system, establish transparent oversight mechanisms, and return the data generated in the process to the nation and society as assets. Limitless Research has begun processing prediction data from markets such as South Korea and Japan into information assets, but more participants are needed. Avoiding the discussion means ceding leadership to others.

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