In-Depth Analysis of Prediction Markets: Mechanisms, Types, and Applications

A prediction market is an open trading platform where participants can trade on the outcomes of specific events. The operation of such markets is similar to a free market economy, where prices are continuously adjusted based on the collective wisdom of participants. Users can trade the probabilities of certain events occurring, and the final market price reflects the expected likelihood of these events.

The core feature of prediction markets is their openness. Unlike traditional gambling, prediction markets start with the same initial odds and then naturally adjust prices based on the knowledge and insights of participants to reflect the most likely outcomes.

Taking the final of the FIFA World Cup in December 2022 as an example, suppose Argentina faces England. The prediction market will create two outcome tokens: ARGWIN( Argentina wins) and ENGWIN( England wins). These tokens are initially traded at a price of 50/50. As participants buy tokens based on their expectations, prices will fluctuate according to supply and demand. Ultimately, the token prices will reflect the most likely outcomes.

Prediction markets can also be seen as derivative markets. As information processors, they are very suitable for the information theory framework. Prediction markets allow participants to trade contracts based on the outcomes of future unknown events, and the market prices formed can be regarded as collective predictions. If these contracts are linked to the prices of certain assets, prediction markets essentially become derivative markets.

Prediction markets have several advantages as derivative markets: they can operate without underlying assets; it is relatively simple to implement automated market making; suitable prediction events can be designed to provide universal products; they have an isomorphic relationship with European options; they are capital efficient; and there is no short squeeze risk.

However, prediction markets also face some challenges: liquidity providers may face high risks; as a novel concept, it takes time for participants to understand; there may be unknown risks that have not yet been discovered.

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 among traders to facilitate price discovery and performs well in high liquidity markets. LMSR is a specially designed automated market maker mechanism aimed at addressing common liquidity issues in prediction markets.

Prediction markets can be divided into various types:

1. Binary market: Involves two possible outcomes, such as "yes" or "no".

2. Classification market: Similar to a binary market, but with more than two options.

3. Scalar ( interval ) market: prediction results within a specific range.

4. Combination Market: Users create multi-level outcome predictions by combining multiple prediction markets.

Compared to traditional opinion polls, prediction markets encourage accurate forecasting through financial incentives, and market dynamics ensure that prices more reliably reflect collective expectations.

Prediction markets are powerful forecasting tools applicable in various fields such as sports events, asset prices, and political decisions. An ideal prediction market platform should create a user-friendly environment, attract liquidity, and provide quick responses, making it easy to create and participate in prediction markets. Decentralization and permissionless participation further enhance the platform's potential, allowing users to discover valuable data. In the future, automated market makers may become increasingly important in ensuring the robustness and accuracy of market predictions.