Prediction markets are marketplaces where people trade on the outcomes of future events. Market prices can indicate what the marketplace believes the probability of the event is. For example, “who will win in a sporting event?" For this sporting event there will be two tokens, one for each team. If the price of token A is higher than token B, it means that the market believes team A has a higher chance of winning.
How prediction markets work
Most prediction markets are a binary option market (e.g., “yes" or “no), where the two options will expire at the price of 0% or 100%. Before expiry, the two assets trade between 0% and 100%, which indicates what the marketplace thinks the odds are. Let’s return to our sporting event example. If the market price of token A is US$0.30 and the price of token B is US$0.70, then the market believes the likelihood of team B winning is approximately 70%.
What are the uses of prediction markets?
Prediction markets can be seen as an extension of derivatives markets. Derivatives, such as futures and options, are used to predict the future price of assets such as oil, gold, stocks, and bitcoin. Prediction markets do the same for events.
Derivatives markets are also used to bet on the probability of some future events, but indirectly. For example, if you believe a certain political party will win the US presidency, you might express that belief by buying or selling certain stocks and commodities. Prediction markets allow people to place bets directly on the probability of the election. In this way, prediction markets can be seen as a “cleaner" way to express your views of the future.
Prediction markets might also be a public good. They have proven to be relatively accurate at predicting future events. Companies such as Google have begun to use prediction markets. Financial institutions pay attention to prediction markets on things like Central Bank rate hikes. News organizations and society at large pay attention to prediction markets on political elections.
Prediction markets are still a young industry. It seems likely that their predictive power will only increase as a more and varied group of people participate.
Centralized or Decentralized Prediction Markets
Many prediction markets today operate within the traditional finance and Web2 ecosystem. Platforms like Kalshi represent a regulated, centralized approach to prediction markets—offering a professional and compliant environment for trading event outcomes. Kalshi, in particular, stands out for being CFTC-regulated, bringing credibility and legal clarity that most platforms lack. However, like other centralized markets, these platforms often face inherent limitations that can affect their predictive accuracy.
One of the main constraints is the cap on how much individuals can stake. Even when someone has strong conviction and the capital to support it, position limits—often below $1,000—can prevent them from fully acting on mispricings in the market. This weakens the market’s ability to reflect true probabilities. Additionally, regulatory requirements like KYC can exclude large segments of the global population, narrowing the participant pool and potentially skewing results. Fees also remain a concern, as seen on platforms like PredictIt, which charges high withdrawal fees.
Decentralized crypto-based prediction markets offer an alternative. They typically allow users to express their views with fewer restrictions, no mandatory KYC, and significantly lower fees. These open-access, low-cost platforms unlock a broader base of participants and allow conviction to scale more freely—strengthening the prediction market’s collective intelligence. While Kalshi plays an important role in bringing event-based trading into the regulatory mainstream, decentralized models aim to complement this by expanding access and flexibility.
