Traditional sports betting allows insiders to exploit static odds. In a liquid prediction market, a large bet based on inside information immediately moves the odds, reflecting that knowledge in the price and eliminating the arbitrage opportunity for the insider.

Thomas Peterffy believes prediction markets provide a clearer consensus than economists' disparate opinions. He envisions economists participating by trading their views, forcing them to put money behind their predictions and letting the market determine their credibility, thus replacing punditry with a single tradable number.

Prediction markets thrive on information asymmetry, mirroring the stock market before 2000's Regulation FD, when selective disclosure was common. This structure means 'sharps' with privileged information will consistently profit from 'squares' (the public), making it difficult for casual participants.

The true value of prediction markets lies beyond speculation. By requiring "skin in the game," they aggregate the wisdom of crowds into a reliable forecasting tool, creating a source of truth that is more accurate than traditional polling. The trading is the work that produces the information.

Financially savvy investors see prediction markets as an inherently superior product. However, real-world data from the UK's Betfair exchange, which only captured 5% of the market over 20 years, suggests the mass market has different preferences.

Rather than killing polling, prediction markets make it better. By creating a tradeable market around outcomes, they introduce a strong financial incentive for pollsters and campaigns to be accurate. This shifts focus from commissioning polls that confirm biases to producing data that can actually win trades, improving information quality.

While framed as a "wisdom of the crowds" tool, prediction markets can be easily manipulated. Wealthy individuals or campaigns can place large bets to create a perception of momentum or inevitability, effectively using the market as a propaganda vehicle to influence public opinion rather than simply reflect it.

Kai Ryssdal dismisses the reliability of prediction markets like Calci, calling them "black boxes" due to unknown bettors and potential manipulation. He cites a personal example where a dark horse candidate for Fed Chair saw his odds inexplicably spike on Calci without any supporting news, only to lose the appointment.

The value of prediction markets comes from aggregating all information, including non-public insights. However, as the Maduro raid case shows, they must actively identify and report illegal insider trading to maintain regulatory compliance and legitimacy, creating a difficult balancing act.