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In prediction markets, large institutional funds like SIG are being outmaneuvered by individual traders known as "sharps." These individuals gain an edge by using agile and sometimes legally gray methods, like aggressive web scraping, which are off-limits to compliance-bound financial firms.

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The rise of accessible prediction markets creates perverse incentives for individuals to profit from insider information or by directly manipulating events. Examples range from a special ops soldier betting on a mission to someone using a hairdryer to spike a temperature sensor, illustrating a new, "democratized" form of sleaze.

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.

A more significant danger than insider trading is that individuals in power could actively manipulate real-world outcomes to ensure their bets on a prediction market pay out. This moves beyond leveraging information to actively corrupting decision-making for financial gain, akin to throwing a game in sports.

An anti-corruption group found that large, long-shot predictions on military attacks are correct 52% of the time. This improbable success rate suggests that a key winning group, aside from bots, are users with non-public, potentially illegal, insider information on geopolitical events.

Platforms like Polymarket effectively financialize all information. This creates opportunities for arbitrage based on publicly available, but not widely known, data. For example, a person won a large bet on the length of the Super Bowl national anthem by simply timing the rehearsals outside the stadium in the days prior.

While praised for aggregating the 'wisdom of crowds,' prediction markets create massive, unregulated opportunities for insider trading. Foreign entities are also using these platforms to place large bets, potentially to manipulate public perception and influence political outcomes.

Unlike stock trading, where hedge funds possess vast data advantages, niche prediction markets on topics like weather or pop culture level the playing field. An individual with deep domain expertise can genuinely have more relevant information than a large financial institution, creating an opportunity for alpha.

The integrity of prediction markets is threatened when individuals can bet on events using non-public information, like knowledge of an impending military operation. This behavior mirrors insider trading and poses a significant ethical and regulatory challenge for the industry.

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.

Tarek Mansour argues traditional finance is dominated by institutions with an information advantage. Prediction markets create an opportunity for individuals with deep, non-traditional expertise—in culture, weather, or technology—to profit from unique insights often overlooked by Wall Street.