From a financial structure perspective, prediction markets and financial derivatives are fundamentally similar. Derivatives such as options and futures are essentially trades based on expectations of future prices or events, while prediction markets trade on the probability of event outcomes. Therefore, prediction markets can be seen as a special type of derivatives market.
In the future, prediction markets may gradually merge with traditional financial derivatives. For example, prediction contracts could be established around macroeconomic data, interest rate policies, corporate performance, or market indices, enabling traders to trade not only asset prices but also the outcomes of events themselves.
This integration could lead to several new market forms:
If prediction markets combine with derivatives markets, their function will extend beyond just forecasting tools and may become part of risk management and hedging strategies.
A key issue in blockchain governance (DAO governance) is how to make decisions. Traditional governance usually relies on voting, but voting results do not always represent the most accurate or effective decisions. Prediction markets offer a new approach to governance by using market mechanisms to forecast the outcomes of decisions, thereby assisting in governance choices.
For example, a DAO could establish a prediction market to forecast whether passing a proposal would increase protocol revenue or grow the user base. Market participants express their expectations for the proposal’s outcome through trading, rather than simply voting for or against it.
Compared to traditional voting, this mechanism offers several potential advantages:
Prediction markets can be used not only for forecasting external events but also for organizational governance and decision-making support.
From a broader perspective, the real potential of prediction markets may not lie in simply forecasting the outcome of an election or the result of a sports game, but in gradually evolving into a completely new mechanism for pricing information. In traditional financial systems, the core function of markets is to price various assets—for example, stock markets assess company value, bond markets reflect interest rates and credit risk, and commodity markets track changes in supply and demand. By contrast, information markets may function to price “the probability of events” and “future expectations.”
In the future information society, information itself could become a tradable asset. In this context, prediction markets would become vital tools for pricing information. Different individuals possess asymmetric information due to their positions and perspectives, and market trading mechanisms can aggregate this dispersed information and externalize it as observable signals through price changes. The resulting market price is essentially the most representative collective judgment about future outcomes after synthesizing vast amounts of information.
If this mechanism continues to develop on a larger scale, future market structures may become more layered and systematic: stock markets would price company value, bond markets would reflect interest rates and credit risk, commodity markets would track real-world supply and demand, while prediction markets would focus on pricing the probability of future events. On this basis, broader information markets could further emerge to assess the value of information itself.
Within such a system, the role of prediction markets would no longer be limited to that of a simple trading platform; they could gradually rise to become a new type of infrastructure beyond the traditional financial system—an information-centric infrastructure that aggregates, prices, and transmits information through market mechanisms, thereby providing society with more efficient signals for future expectations.