Prediction Market: The Financial Innovation of Collective Intelligence

The prediction market is an innovative financial instrument that allows participants to trade on the outcomes of specific events. These markets operate similarly to a free market economy, with prices continuously adjusted based on the collective judgment of participants. Users can trade the probabilities of certain events occurring, and the final market price reflects the expected likelihood of these events.

The openness of prediction markets is one of its most critical features. Unlike traditional gambling, prediction markets start with the same odds and then naturally adjust the prices based on participants' knowledge and insights to reflect the most likely outcomes.

Taking the FIFA World Cup final in December 2022 as an example, suppose it is Argentina against England. In the prediction market, two outcome tokens can be created: ARGWIN( Argentina wins) and ENGWIN( England wins). These tokens initially trade at the same price, such as 50/50. As participants buy based on their expectations, the prices will fluctuate according to supply and demand. If more people buy ARGWIN, its price will rise while ENGWIN will fall. Over time, the market will self-adjust, and the token prices will ultimately reflect the most likely outcome.

Prediction markets can also be seen as a type of derivative market. As information processors, they can be designed within an information theory framework, making them particularly suitable for this model. Prediction markets allow participants to trade contracts based on the outcomes of future unknown events, and the resulting market prices can be viewed as collective predictions. If these contracts are linked to the prices of certain assets, prediction markets effectively become derivative markets.

Prediction markets, as derivative markets, have several advantages: they can operate without underlying assets, allow for simple automated market-making, are multifunctional, are isomorphic to European options, have high capital efficiency, and carry no short squeeze risk, among others. However, there are also some disadvantages, such as liquidity providers facing high risks, market participants needing time to understand their mechanisms, and the potential for unknown risks.

The two main mechanisms that support the operation of prediction markets are continuous double auctions (CDA) and logarithmic market scoring rules (LMSR). CDA relies on direct interaction between traders to facilitate price discovery and is suitable for high liquidity markets. LMSR, on the other hand, is a specially designed automated market maker mechanism aimed at addressing common liquidity issues in prediction markets.

CDA performs well in markets with sufficient participants, facilitating effective price discovery. In contrast, LMSR has advantages in environments with limited liquidity, as its automated market-making feature ensures that trades can occur at any time and helps prevent extreme price fluctuations.

Prediction markets can take various forms, including binary markets, categorical markets, scalar ( range ) markets, and composite markets. Each form is suitable for different scenarios, ranging from simple yes/no predictions to complex multivariable predictions.

Compared to traditional polls, prediction markets encourage accurate predictions through financial incentives, and the natural dynamics of the market ensure that prices can continuously adjust, thereby providing more reliable data.

Overall, prediction markets are a powerful tool for predicting various outcomes. The goal of any prediction market platform should be to create a user-friendly environment that attracts liquidity and provides quick responses, making the creation and participation in prediction markets easy. Decentralization and permissionless participation further enhance the platform's potential, enabling users to discover valuable data about the world. As the field continues to evolve, automated market maker mechanisms may become increasingly important in ensuring the robustness and accuracy of market predictions.