Prediction Markets as Emerging Attention Economy: A Clear Contrast with Memecoins
Prediction markets have grown rapidly. In the first ten months of 2025, global trading volume reached $27.9 billion, a 210% increase from 2024. Like Memecoins, prediction markets attract a high concentration of small-cap participants. However, the two operate on fundamentally different mechanisms.
In prediction markets, participants can distribute small amounts across multiple events, with transparent odds and clear downside. Event structures allow informed users to convert domain knowledge into measurable returns—particularly in lower-liquidity markets where information gaps create opportunities.
Memecoin trading follows a different pattern. On Pump.fun, 10,417 tokens are created daily, 98.6% of which are identified as manipulative and typically last less than three months. Prices move primarily on social momentum rather than probability. Information asymmetry heavily favors token creators, leaving ordinary users dependent on hype cycles rather than informed insight.
Although prediction markets also spread through social channels, their traction comes from evolving event dynamics, not emotional spikes. For most participants, prediction markets function as information-based competitions, while Memecoins resemble attention-driven lotteries.
Rapid Growth with Underlying Structural Fragility
Despite rising participation, prediction markets remain structurally fragile. Liquidity on many platforms is still incentive-dependent; some previously spent more than $50,000 per day on market-making subsidies, with depth shrinking once incentives declined. Losing outcomes settling to zero makes it difficult for markets to accumulate lasting depth, and as events near resolution, informed traders increasingly capture favorable pricing—raising losses for market makers.
Other structural limitations persist: binary formats offer limited expressiveness; discovery is weak in thin markets; permissionless event creation is constrained; and oracle settlement processes face delays or manipulation risks. These challenges indicate that prediction markets are still in the early stages of their infrastructural development.
Structural Innovation Signals the Next Phase
To address these constraints, new system designs are emerging. Just-in-time liquidity injects capital only when needed, improving efficiency. Continuous combinatorial markets reduce fragmentation by allowing views to be expressed across a continuous range rather than through isolated binaries.
New prediction structures—including perpetual contracts built on prediction-market data and rapid-settlement binary formats—expand expressive capacity beyond traditional designs. Distribution is also evolving: probability-path charts fit naturally into social feeds, and new platforms increasingly embed trading flows into social networks, transforming prediction markets into “financial formats” that circulate through attention channels.
These innovations do not solve all structural challenges immediately, but they mark a shift toward more scalable architectures.
The Rise of Attention-Based Finance
HTX Research points out that attention assets are becoming the third major asset class, following cash flow assets and supply-demand assets. Representative tokens within the category include BAT, KAITO, and more. According to HTX data, BAT rose by over 30% over the last 30 days, and KAITO was once a market hit in H1 2025.
Besides these projects, HTX Research suggests that prediction markets have the potential to become core pricing infrastructure for attention assets. Existing user-generated attention assets, such as NFTs or creator tokens, start from zero and cannot capture established cultural relevance. Prediction markets, by contrast, generate time-based prices and liquidity signals that can be aggregated into an attention index reflecting real-world visibility.
Such an index offers several advantages: attempts to manipulate it require real capital; existing attention can be represented without beginning from zero; and participants can take long or short positions on attention shifts. As this framework matures, prediction markets may evolve from tools for forecasting outcomes into infrastructure capable of measuring and pricing cultural relevance—supporting instruments such as Attention Perpetuals.
Conclusion
Prediction markets are transitioning from rapid growth to structural refinement. While challenges persist, innovation across liquidity, expressiveness, and distribution is reshaping market design. As attention-based assets become more clearly defined, prediction markets may increasingly serve as the connective layer between cultural and financial value.
Compared with the sentiment-driven volatility of Memecoins, prediction markets offer information-driven, probability-based participation. As their architecture matures, their role in the digital asset ecosystem is likely to expand significantly.
About HTX Research
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