The 2026 financial year kicks off: Prediction markets are becoming the next fertile ground for DeFi.

Since the article "Where Should the Chinese Prediction Market Explore?", prediction markets have gained mainstream acceptance globally. Referring to Bitcoin and stablecoins, crypto products that achieve Proof-of-Fact (PMF) are recognized by the market as a new sector, attracting continuous capital inflows.

Benefiting from the inherent platform monopoly effect of the prediction market, it has become a consensus within the industry to provide peripheral services around it, so as to cultivate it into a natural petri dish for capturing the ecosystem outside the industry, thereby constructing a hierarchical ecosystem of the subject, the periphery, and the outer periphery.

After describing the basic structure and direction of the prediction market above, we will try to analyze its existing peripheral services. In addition to copycat platforms, tools, and rebates, what other directions can support peripheral business models with high market value?

Premature prediction market

Prediction markets are uncertain markets with high certainty. For example, the dates and participating teams of the World Cup, as well as the US midterm elections and the US presidential election, are highly controllable in terms of pre-participants, basic dates, and rules.

However, the winning team of the World Cup cannot be predetermined, otherwise it would be a conspiracy. Therefore, it is an uncertain information game, and its fundamental nature will change as more and more information factors are added.

For example, during the 2024 US presidential election, a significant number of bets occurred within 5 days of the expiration date. In on-chain transactions, users' bullish and bearish sentiments directly affect the bullish and bearish markets, converging into self-fulfilling prophecies.

Current prediction markets are moving in this direction; for example, the CEO of Coinbase noticed that people were predicting his statements and therefore "cooperated" with the eventual outcome.

Image caption: Data required for prediction. Image source: https://brier.fyi/

Before market prediction, polls and the media played such a role. It was not that polls tested voters' preferences, but rather that they guided people's choices. Therefore, in the Western context, market prediction is regarded as an information tool, on which functions such as insurance, hedging, and taxation are added.

Therefore, prediction markets are far more sensitive than trading tools. Just as TikTok wasn't besieged by both parties because of its popularity, prediction markets inherently cannot be fragmented.

• Information discovery requires strategic interaction based on real, real-time data to improve its accuracy, and information leads to more concentrated traffic.
• The US election market is highly mature, and only those with a Western background can achieve a balance of power with the political system without breaking it, thus becoming a new channel for information.

Based on this, Polymarket and Kalshi are information hubs that are "mature from birth," which is the fundamental reason why US capital continues to invest in and drive up their valuations, rather than using a race-the-horse mechanism like Binance.

Of course, none of this concerns us. What concerns us is how to capitalize on the frenzied FOMO (Fear of Missing Out) market.

Image caption: Prediction market surroundings. Image source: @zuoyeweb3

Overall, the market has evolved into four models:

• Copycat platforms other than Polymarket and Kalshi require investments at the level of Perp DEX, as well as high compliance costs in the US market. Overall, they will move towards the TGE track and have almost no real adoption rate.
• Asset-layer innovations for existing prediction platforms:

• DeFi-ization of betting assets in the prediction market, such as Gondor allowing them to be used as collateral for lending, and Space adding 10x leverage to them, is essentially a violent incorporation of DeFi elements;
• There are also prediction markets for innovative assets, such as 42 Space, which generates prediction topics directly based on social media feeds, attempting to differentiate themselves from existing platforms.
• Mainstream Web3/2 financial trading super apps such as Coinbase and Robinhood complete their trading offerings.

• Customized tools for specific groups and needs in the prediction market, such as high-frequency trading, multi-platform arbitrage trading or aggregated trading terminals, LP mining or paid small group tools, and prediction market data and information aggregation and analysis platforms.
• KOLs and rebate platforms, such as mobile trading platforms like Based and Phantom Wallet, as well as various social sharing and rebate KOLs or communities.

In the above paradigms, the investment in the prediction market itself is too large, and due to political considerations, there is almost no high valuation prospect for new forces. Secondly, the tools and rebates will show a cycle with the investment in the prediction market and the change of hot spots.

The only worthwhile area for business investment is the DeFiization of assets on prediction platforms. While waiting for the results, the betting assets are in a dormant state, which may be the most noteworthy high-quality assets in DeFi.

A win-win cross-market arbitrage mechanism

Facing traffic services provided by giants is always a delicate matter. On the one hand, giants need third parties to increase platform traffic; on the other hand, they don't want third parties to develop brand effects.

This was the dilemma faced by early e-commerce traffic stations: they had to maintain good relationships with platforms, sellers, and buyers. Sellers needed third-party traffic stations to enhance their competitiveness, while buyers wanted to get discounted prices.

Image caption: Image source: @zuoyeweb3 (Third-party service)

Traffic sites start from the perspective of rebates, and the platform develops corresponding sharing/purchasing/rebate tools. As long as the natural traffic that the seller receives after exposure is greater than the promotional discount, the whole business can operate sustainably.

• Sellers need to rely on platforms to receive organic traffic, as the costs of operating their own brands and channels are too high.
• Buyers need the platform to handle after-sales service and protect their rights, and the payment process also requires platform guarantees.

Referring to the three-way battle among e-commerce platforms—Taobao, JD.com, and Pinduoduo—the market for new e-commerce platforms is too narrow. The e-commerce market naturally needs to satisfy the dual structure of "brand merchants + long-tail traffic." Newcomers cannot generate economies of scale by capturing brand merchants or focusing on niche markets.

Ultimately, Taobao relied on Tmall to capture and retain its entire customer base from the high-end market, while Pinduoduo relied on the national-level application WeChat to drive traffic from rural China to the world. Only JD.com, which focused on brands, was caught in a dilemma.

Here we compare the rebate mechanisms of exchanges. Rebate KOLs and exchanges pursue the number of retail investors following their trades, and the profits and losses of retail investors do not affect the trading mechanism. This is different from e-commerce rebates, where users have an initial need to purchase goods, and giving users discounts is beneficial to the promotion effect of traffic stations and sellers.

From this perspective, the Builder mechanism of Hyperliquid and Polymarket does not solve the above problems; the growth it promotes can only be an increase in trading volume.

This is not to say that the growth in trading volume is unimportant, but it will still lead to the waste of idle funds. In fact, the more trading volume there is, the more idle funds there will be, which is not a good thing for the financial industry that pursues capital efficiency.

If the market cannot break free from the limitations of the growth logic of CEX/DEX, then the prediction market will quickly reach its peak, because the number of public events available for trading is ultimately limited, and the smaller and more instantaneous the event, the more it will favor the market makers, and it will truly move towards the exchange track.

Information games are the essence of prediction markets. In the process of betting and maturity, funds are tied up. How to make good use of these tied-up funds is the underlying driving force behind the mutual attraction between prediction markets and DeFi.

Image caption: Leveraging forecasted assets. Image source: @zuoyeweb3

Do not attempt to interfere with the user's normal betting experience. In the existing discussions about leverage in prediction markets, there are mainly two trends:

1. Gondor's interception operation forces users to stake their positions in DeFi after placing bets. Regardless of liquidity management and APY calculation, simply changing users' purpose is already twice as difficult, and it is easy to embark on the irreversible path of attracting deposits with high interest rates.
2. Kaleb Rasmussen of Messari attempted to price the “jump risk” of prediction markets. As mentioned earlier, price changes in prediction markets can instantly return to 1 or 0. His mathematical explanation is brilliant, but it is quite difficult to implement in real-world financial engineering.

Based on existing practices, I boldly propose a simpler way to achieve transparent leverage in DeFi without interfering with the user experience for founders to consider: a cross-market arbitrage mechanism similar to Taobao affiliate marketing, which allows for arbitrage between the audience of the prediction market and the DeFi audience.

1. The platform offers a prediction market order placement service, allowing users to place orders for 0 or 1 positions at a discounted price, obtaining better market prices. This benefits the platform by providing lower financing costs, and prediction markets such as Polymarket gain more traffic.
2. The platform or prediction market LP/MM acts as the treasury manager. After placing bets, users deposit them into the treasury of a protocol that partners with the prediction market, such as Morpho, and earn DeFi stack rewards.

In the above process, the user's betting experience is not interfered with at all. As long as the platform's discounted price cost is less than the yield in the DeFi stack, the scale utility will take effect. The user will still get the loss or profit of their bet in the end. However, unlike the transaction rebate mechanism, the user places orders based on their own judgment.

Unlike xUSD, which involves unlimited issuance and leverage, Polymarket's USDC is real and its only risk lies in the operator's skill level.

• Prediction market platforms: Integrate themselves into a broader DeFi stack, increasing platform trading volume without compromising user experience;
• Manager + LP/MM: By making good use of idle funds and funds with fixed maturity dates, a brand-new model that goes beyond short-term arbitrage can be built;

Similar to the rebates offered by third-party traffic sites in e-commerce, buyers will still have any transactional relationship with the platform and sellers. Similarly, Yes/No bettors in the prediction market will also have transactional relationships with Polymarket, which is unrelated to the vault manager.

Furthermore, Polymarket remains at the core of the entire transaction process. Thanks to Morpho's open architecture, even bad debts will be settled through normal liquidation procedures, minimizing the platform's liability.

Conclusion

The true value of the prediction market lies in the accumulation of funds, with clear maturity dates and corresponding asset reserves. If Polymarket is to outperform Kalshi in terms of capital efficiency, its scale expansion has reached its limit.

In other words, compared to trading assets, Wall Street and the cryptocurrency market are currently in a phase of irrational frenzy regarding the pricing of information. Whether it's TGE or an IPO, or issuing stablecoins or building their own L1/L2, these are all expected and routine actions.

Ahead of the uncertain TGE/IPO date, Polymarket needs to strengthen its surrounding ecosystem to boost trading volume and counter Kalshi. On-chain programmability and composability of funds are the solution for Polymarket's external traffic.

The biggest financial opportunities in 2026 are the cyclical fluctuations of the midterm elections and the World Cup, FIFA's appeasement of Trump, and regulators' approval of DeFi and gambling, making it a truly big year for finance.