Prediction Market: The Power of Collective Intelligence

A prediction market is a special financial market where participants trade to predict the outcomes of specific events. These markets operate similarly to a free market economy, with prices adjusting based on the collective judgment of participants. In a prediction market, 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 important features. Unlike traditional betting, prediction markets start with the same odds and then adjust naturally based on the knowledge and insights of participants to reflect the most likely outcomes.

For example, in the FIFA World Cup final in December 2022, suppose Argentina is facing England. The prediction market will create two outcome tokens for trading: ARGWIN( Argentina wins ) and ENGWIN( England wins ). These tokens initially trade at the same price, such as 50/50. As participants purchase tokens based on their expectations, 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 token prices will reflect the most likely outcomes.

Prediction markets can also be viewed as derivative markets. As information processors, prediction markets are particularly suited to the framework of information theory. They allow participants to trade contracts based on the outcomes of future unknown events, with the market prices formed being seen as collective predictions.

Prediction markets, as a derivative market, have several advantages: they can operate without underlying assets; it is relatively simple to implement automated market maker (AMM); they are multifunctional; they have a isomorphic relationship with European options; they are capital efficient; and there is no risk of a short squeeze. However, there are also some disadvantages, such as liquidity providers facing risks, the market concept being relatively new and requiring learning, and the possibility of unknown risks.

Prediction markets primarily operate through two mechanisms: continuous double auction ( CDA ) and logarithmic market scoring rule ( LMSR ). CDA relies on direct interaction among traders to facilitate price discovery and performs excellently in 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. LMSR provides continuous liquidity, ensuring that traders can execute trades at any time without waiting for matching orders from other participants.

Prediction markets can be divided into several forms: binary markets ( with two possible outcomes ), categorical markets ( with multiple options ), scalar markets ( with outcomes within a specific range ), and combinatorial markets ( that combine multiple prediction markets ). Each form is suitable for different scenarios.

Compared to traditional polls, prediction markets encourage accurate predictions through financial incentives, and market dynamics ensure that prices can self-correct, providing more reliable data.

A prediction market is a powerful tool that can be used to forecast various outcomes. An ideal prediction market platform should create a user-friendly environment, attract liquidity, and provide quick responses. Decentralization and permissionless participation further enhance the platform's potential, allowing users to discover valuable data about the world. Understanding the strengths and weaknesses of CDA and LMSR mechanisms is crucial for designing effective prediction markets to ensure accurate aggregation of information and generate reliable predictions.