In the past two years, it is predicted that the market in the United States will experience a large-scale outbreak, and the trading targets will no longer be limited to sports events and film awards, gradually extending to geopolitical, macro events, technological iteration, industry trends and other comprehensive scenarios. In the eyes of the public, it is an emerging track for the future outcome of the game; However, from the research perspective of a16z, the essence of predicting the market goes far beyond "event betting". It is an efficient infrastructure that relies on market-oriented mechanisms to aggregate global information, quantify future probabilities, and output accurate expectations. It fills the natural gap of traditional research and expert analysis, and is becoming a new core tool for human observation, prediction, and adaptation to the future.

1、 Essence traceability: The prediction market is the purest information pricing market

From the perspective of the underlying logic of economics, predicting the market is not an alternative innovation, but an extension and maximization of traditional market functions. The core values of traditional markets are twofold: firstly, efficient allocation of resources, allowing goods, services, and capital to flow towards optimal scenarios; The second is information aggregation pricing, which aggregates fragmented information, individual judgments, and market sentiment into a unified and referenceable price signal through the trading behavior of a large number of participants.

The prediction market is a specialized pricing market that focuses on the outcome of future events. The platform issues exclusive underlying contracts around specific, implementable, and verifiable future events. Participants buy and sell contracts based on their own knowledge, information reserves, and professional judgment, and the final contract price will intuitively reflect the market consensus probability of the event. Simply put, the stock market prices future profits for companies, commodities price supply and demand trends, and predicting the market accurately prices the probability of future events occurring.

This model has already been implemented in diverse scenarios. Enterprises use internal market forecasting to summarize frontline employee information and predict the progress of new product launches and the probability of project implementation; In the field of scientific research, by predicting the market, screening replicable experimental conclusions, and optimizing the allocation of scientific research resources; Mainstream media has also begun to collaborate with the prediction market, supplementing traditional sources with collective intelligence to make event analysis more comprehensive and objective.

2、 Operating mechanism: Price is probability, trading is opinion expression

Compared to traditional financial assets, predicting market trading logic is simpler and pricing is more accurate, completely solving the pain point of vague signals in traditional markets. The prices of assets such as crude oil and stocks are affected by multiple factors such as supply and demand, policies, emotions, and funds. Price fluctuations cannot correspond to a single event, and investors find it difficult to accurately decipher the core logic behind them.

The contract rules for predicting the market are highly clear and the results are unique: the contract returns are deeply bound to a specified single event, and settlement is completed upon the event landing, with prices purely corresponding to the probability of the event occurring. Taking the contract of "whether the Strait of Hormuz is normally open for navigation during specific periods of time" as an example, a single contract stipulates that fixed income can be redeemed upon the occurrence of an event. If the contract price is 0.5 US dollars, it represents an overall market judgment that the probability of the event occurring is 50%.

Participants complete trading games based on cognitive differences: if the trader has exclusive information and judges that the true probability is higher than the market price, they will buy the contract, pushing up the price and market expectations; If it is judged that the market valuation is overvalued, it will sell or short, correcting the probability expectation of overvaluation. Every transaction is an input of information, continuously refining market consensus and making prices infinitely close to the true probability.

3、 Core advantage: Overcoming the three major underlying barriers of traditional research and judgment models

Compared with traditional forecasting methods such as public opinion surveys, expert predictions, and data analysis, the forecasting market has an irreplaceable core advantage, which is also the core reason for its rapid rise.

Firstly, directly quantifying probability results in more intuitive and accurate outcomes. Public opinion polls can only output the proportion of opinions expressed, and require complex statistical calculations to derive probabilities, resulting in human error and sample bias. And predicting the market does not require secondary processing, the contract price directly corresponds to the probability of event occurrence, and the output results are standardized and can be directly implemented for reference.

Secondly, real-time dynamic iteration to adapt to changes in information. Traditional polls and expert judgments are mostly static snapshots that can only reflect market awareness at a certain point in time, and cannot be updated in a timely manner when new information appears. The predictive market is a 24/7 dynamic market, where new information, trends, and new participants continue to enter the market. Prices and probability expectations iterate in real-time, always keeping up with the latest market changes.

Thirdly, real monetary incentives are used to eliminate ineffective noise. Traditional survey participants do not need to bear the cost and are prone to answering questions arbitrarily or emotionally, making it difficult to guarantee the authenticity of the data. However, predicting that market participants need to invest real funds and assume losses due to misjudgment will force participants to delve deeper into information, make rational judgments, respect the market, and filter out ineffective emotions and false views to the greatest extent possible. During the 2024 US presidential election, some market participants actively broke through the limitations of traditional polls, conducted refined research, obtained exclusive information, and profited from the game, fully demonstrating the value of this mechanism.

In addition, predicting market coverage scenarios has no boundaries. Traditional stock markets and commodity markets can only cover macro mainstream tracks, and a large number of niche, segmented, and refined events cannot be priced. The threshold for predicting the market is extremely low, and anyone can initiate the market and create contracts, covering various long tail scenarios such as AI model ranking, segmented industry iteration, and niche policy implementation, filling the pricing gap in traditional financial markets.

4、 Development Traceability: A Century of Evolution, From Academic Theory to Large Scale Implementation

Predicting the market is not an emerging concept, and its embryonic form can be traced back to 16th century Europe. At that time, the market had already predicted the candidate for the Pope through trading games, forming an early group prediction mechanism. The modern forecasting market relies on economics, statistics, and computer science to form a complete academic system. In the 1980s, scholars Charles Prot and Sayam Sanders established a standardized theoretical framework, laying the foundation for industry development.

Subsequently, the world's first modern forecasting market, the Iowa electronic market, was launched, relying on the Internet to break geographical restrictions, gather global fragmented information, and transform decentralized individual cognition into a unified market consensus. Up to now, with the development of encryption technology and a complete compliance system, the prediction market has completely broken through niche academic scenarios and moved towards commercial, large-scale, and universal applications. Sports events are catalysts for the popularization of the industry, and long tail scenarios such as geopolitics, technology industry, and macroeconomics are becoming the core increments of industry growth.

5、 Existing Shortcomings: Four Core Challenges Hindering Industry Explosion

Despite its advanced logic and significant advantages, the prediction market has not yet fully unleashed its potential. Multiple issues such as infrastructure, market mechanisms, participant structure, and external interference remain bottlenecks that the industry urgently needs to overcome.

Firstly, there is the issue of infrastructure and settlement disputes. The underlying systems for verifying event results, achieving market consensus, auditing transaction traceability, scaling up dispute resolution, and preventing malicious manipulation are not yet fully developed. When there are differences in contract settlement and the market is subject to human intervention, the industry does not have a mature mechanism to quickly resolve risks, which affects market credibility.

Secondly, the prediction bias is caused by the imbalance of participant structure. The accuracy of predicting the market relies on the input of effective information. If the group that holds the core information chooses to wait and see, and ordinary participants dominate the trading, the market price will seriously deviate from the true probability. A typical case is the 2016 Brexit and Trump's first election as the President of the United States. At that time, market participants failed to capture the implicit signals of the rise of populism, which directly led to a significant underestimation of the probability of events occurring in the predicted market.

Furthermore, there is the risk of insider information and event manipulation. If personnel with insider information enter the market for trading, it will undermine market fairness; A more extreme scenario is that insiders profit from their own transactions through financial games and human intervention in the course of events. This behavior will completely destroy market trust, lead to collective withdrawal of ordinary participants, and ultimately trigger market collapse.

Finally, there is the risk of public opinion manipulation and price distortion. Some institutions and teams can deliberately hype up contract prices through their financial advantages, create false market consensus, guide public opinion, and create false expectations. For example, the campaign team can create a leading market atmosphere and mislead public perception through funding support. Although it is predicted that the market has the ability to self correct and overvalued or undervalued prices will eventually return to rationality, short-term price distortions can still disrupt market order and mislead market judgments.

6、 Industry outlook: Improve the rule system and become the core infrastructure for future research and judgment

The core value of predicting the market is to use market-oriented, incentive based, and dynamic mechanisms, gather collective wisdom, and solve the inherent shortcomings of human linear prediction, static analysis, and emotional judgment. It is a new type of prediction tool that adapts to the complex and ever-changing era.

The core development direction of the future industry will focus on improving rules and optimizing mechanisms: by refining participant admission standards, optimizing contract design, building standardized settlement systems, improving audit supervision mechanisms, avoiding manipulation risks, repairing market weaknesses, and enhancing industry transparency.

With the continuous improvement of infrastructure, the gradual implementation of compliance systems, and the continuous maturity of market mechanisms, it is predicted that the market will break free from the label of "niche game tools" and be widely used in core scenarios such as macro analysis, industry forecasting, policy analysis, and risk warning. It has become an important infrastructure for human observation of the future, coping with uncertainty, and grasping the trend of the times.、