Prediction Markets: Navigating Challenges and Opportunities in Crypto

Prediction Markets: A Closer Look

Prediction markets are undeniably one of the most watched sectors in the crypto industry. The leading project, Polymarket, boasts over $36 billion in accumulated trading volume and recently completed a strategic funding round at a $9 billion valuation. Additionally, platforms including Kalshi (valued at $11 billion) have received substantial capital injections.

Challenges Facing Prediction Markets

Despite the continuous influx of capital and impressive data growth, prediction markets, as trading products, still face numerous challenges. This article aims to offer different perspectives, moving beyond the prevailing optimistic sentiment.

1. The Non-Continuous Nature of Events

Prediction markets rely on events, which by nature are non-continuous and non-replicable. Unlike asset prices such as stocks and foreign exchange that change over time, prediction markets depend on limited and discrete real-world events. This makes them low-frequency compared to traditional trading. The number of events with widespread attention, clear outcomes, and settlement within a reasonable timeframe is extremely limited—presidential elections every four years, the World Cup every four years, the Oscars once a year, and so on. Most social, political, economic, and technological events do not meet sustained trading demand. This limited number of low-frequency events makes it difficult to build a stable trading ecosystem. In other words, the low-frequency nature of prediction markets cannot be easily changed by product design or incentive mechanisms. This underlying characteristic dictates that trading volume cannot remain high in the absence of significant events.

2. Absence of Fundamentals

Unlike stock markets, which derive value from the intrinsic value of companies, including future cash flows, profitability, and assets, prediction markets rely on “users' interest in the outcomes of events themselves.” In this context, the amounts individuals are willing to bet are closely related to the event's importance, market attention, and timeframe. Rare and high-attention events such as finals and presidential elections attract large amounts of capital and attention. Naturally, an average fan is more likely to care about the outcome of the annual finals and bet heavily on it but is unlikely to do the same in the regular season. On Polymarket, the 2024 presidential election events account for over 70% of the platform's total open interest. At the same time, the majority of events remain in a state of low liquidity and high bid-ask spreads. From this perspective, it is difficult to expand the size of prediction markets exponentially.

3. Gambling Nature

Prediction markets possess a gambling nature, but they struggle to achieve the same level of retention and expansion as traditional gambling. The true addiction mechanism in gambling lies in instant feedback—slot machines every few seconds, Texas Hold'em poker every few minutes, and contract and memecoin transactions changing rapidly every minute. In contrast, prediction markets have a long feedback cycle, with most events taking weeks or months to settle. If the events are fast feedback, they may not be interesting enough to justify large bets. Immediate positive feedback significantly increases the rate of dopamine release, reinforcing users' habits. Delayed feedback cannot form stable user retention.

4. Information Asymmetry

In some types of events, there is significant information asymmetry among participants. For competitive sports events, in addition to the apparent strength of the teams, there is also significant reliance on the athletes' performance on the field, leading to a great deal of uncertainty. However, political events involve black-box processes such as insider information, channels, and personal connections, giving insiders a tremendous informational advantage. For example, external participants find it difficult to access information about vote counting processes, internal polls, and organization of key regions in elections. To date, regulatory bodies have not clearly defined “insider trading” in prediction markets, leaving this part in a gray area. In general, in these types of events, the information-disadvantaged party can easily become a liquidity provider for insiders.

5. Linguistic Ambiguity

Due to ambiguity in language and definition, it is difficult to make prediction market events completely objective. For example: Whether “Russia and Ukraine will cease fire in 2025” depends on the statistical metrics used; whether “cryptocurrency ETFs will be passed at a certain time” involves full passage, partial passage, or conditional passage, and so on. This involves the issue of “social consensus”—in cases where forces are evenly matched, losers will not honestly admit defeat. This ambiguity requires platforms to establish a dispute resolution mechanism. Once prediction markets touch linguistic ambiguity and dispute resolution, they cannot fully rely on automation or objectivity, allowing room for human manipulation and corruption.

6. User Biases

The core value proposition of prediction markets is “the wisdom of crowds,” that is, low trust in media and mainstream speaking rights. Prediction markets can aggregate the best information from around the world to achieve a collective consensus. However, before prediction markets reach extremely large-scale adoption, this “information sampling” must be biased, and the samples are not diverse enough. The user base of prediction market platforms may be highly homogeneous. For example, in the early stages of prediction markets, it will certainly be a platform primarily composed of cryptocurrency users, who may have highly convergent views on political, social, and economic events, thereby forming an information cocoon. In this case, the market reflects the collective biases of a particular circle, which is far from “the wisdom of crowds.”

Conclusion

This article is not intended to diminish prediction markets but aims to maintain calmness amidst rising sentiments, especially after experiencing the rise and fall of popular narratives such as ZK and GameFi. Over-reliance on special events such as elections, short-term sentiment on social media, and airdrop incentives often amplify data appearances and are insufficient to support long-term growth judgments. However, from the perspective of user education and acquisition, prediction markets remain significant in the next three to five years. Similar to on-chain yield-generating savings products, they have an intuitive product form and low learning cost, and they are more likely to attract users from outside the circle to the cryptocurrency ecosystem than on-chain trading protocols. Based on this, prediction markets are likely to develop further and become to some extent an entry-level product for the cryptocurrency industry. Future prediction markets may also occupy certain vertical fields, such as sports and politics. They will continue to exist and expand, but they do not have the basic conditions for exponential growth in the short term. We should think about prediction market investments with a cautiously optimistic perspective.