The prediction market's yes+no=1 seems to have nothing to do with Hayek. However, Hayek's "The Use of Knowledge in Society" once proposed that the core economic challenge society faces is aggregating knowledge dispersed among individuals, rather than simply resource allocation. In his view, information is fragmented, individualized, and constantly changing. He believed that planners cannot fully grasp all information, and at this point, market prices serve as a signal that can efficiently aggregate this dispersed knowledge, ultimately forming collective wisdom. The formula yes+no=1 is the core mechanism of the prediction market, which resonates with Hayek's views. Both agree that prices are a better way to aggregate knowledge. The sum of the prices of yes and no shares equals 1, representing a binary hedge of event probabilities, where participants aggregate different individual information through buying and selling, allowing prices to reflect collective predictions in real-time. With the launch of prediction markets, Hayek's original ideas are no longer abstract concepts but have truly materialized in reality. Specifically, why does yes+no=1 reflect Hayek's "knowledge aggregation" theory? Hayek emphasized that markets aggregate information through self-interested behavior (pursuing profit) without planner involvement; in prediction markets, traders buy and sell shares based on their personal information and understanding, with prices automatically adjusting to probability estimates. If the yes price is 0.7, it means there is a 70% probability that the event will occur. This is similar to what Hayek referred to as "price signals." Information dispersed among individuals is transformed into collective predictions through this mechanism. Moreover, this formula is a mandatory zero-sum game, where the incorrect lose money, and the correct predictors profit. In simple terms, everyone participates with real money, which incentivizes everyone to contribute genuine opinions, making this mechanism superior to simple polls or expert opinions. Of course, the above are all advantages. There are certainly limitations as well. For example, prediction markets can be subject to insider manipulation, thin market biases, etc., and have already experienced this multiple times in the market.