The 2026 Financial Year Opens: Prediction Markets Are Becoming the Next Fertile Ground for DeFi

Since the article “Where Should the Chinese Prediction Market Explore Next” was published, prediction markets have entered the mainstream worldwide. Referencing Bitcoin and stablecoins, crypto products that achieve PMF will be recognized by the market as a new track, receiving continuous funding.

Thanks to the inherent platform monopoly effect of prediction markets, surrounding services around them have become a consensus within the industry, aiming to cultivate them into natural incubators for capturing external ecosystems, thereby building a hierarchical ecosystem of core—peripheral—outer layers.

After outlining the basic pattern and direction of prediction markets above, let’s analyze their existing peripheral services. Besides imitation platforms, tools, and rebate programs, what other directions can support high-market-cap peripheral business models?

Mature Prediction Markets

The world may end, but progress marches on.

Prediction markets are highly deterministic uncertain markets. For example, they pre-define the dates and participating teams of the World Cup, the US midterm elections, and the US presidential election, with participants, basic dates, and rules being highly controllable in advance.

However, the winning team of the World Cup cannot be predetermined; otherwise, it would be a black box. Therefore, it remains an uncertain information game, constantly changing as new information factors are added.

For instance, during the 2024 US presidential election, a significant portion of bets occur within five days before expiration. On-chain trading allows users’ bullish or bearish sentiments to directly influence the market, converging into self-fulfilling prophecy.

Current prediction markets are developing in this direction. For example, Coinbase CEO noticed that people are predicting his statements, thus “cooperating” with the eventual outcome.

Image caption: Prediction requires data. Image source: https://brier.fyi/

Before prediction markets, polls and media played similar roles—not because polls tested voters’ tendencies, but because polls guided people’s choices. In Western contexts, prediction markets are viewed as information tools, layered with functions like insurance, hedging, and taxation.

Therefore, prediction markets are far more sensitive than trading tools. Just as TikTok is not surrounded by bipartisan opposition due to trivial entertainment, prediction markets are inherently non-fragmentable:

• Information discovery must be based on real-time, authentic data to improve accuracy, with information driving more concentrated traffic;
• The US election market is highly mature, achievable only within Western political systems, serving as a new information channel without disrupting the system.

Based on this, Polymarket and Kalshi are “born mature” information hubs, which explains why US capital continues to push their valuations higher, unlike Binance, which relies on a horse race mechanism.

Of course, this has little to do with us. What concerns us is how to leverage the FOMO in crazy prediction markets.

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

Overall, the market has evolved into four models:

• Imitation platforms outside Polymarket and Kalshi require Perp DEX-level investments and face high compliance costs in the US market, generally heading toward TGE tracks with almost no real adoption;
• Asset layer innovations on existing prediction platforms:
  • DeFi-ify betting assets on prediction markets, e.g., Gondor allowing them as collateral for lending, Space adding tenfold leverage—essentially injecting DeFi elements forcibly;
  • New assets like 42 Space, which generate prediction topics directly from social media information streams, attempting to differentiate from existing platforms;
  • Mainstream Web3/2 financial super apps like Coinbase/Robinhood, filling gaps in trading types.
• Custom tools for specific prediction market audiences and needs, such as high-frequency trading, multi-platform arbitrage, or aggregated trading terminals, LP mining, or paid small-group tools, as well as prediction market data and analysis platforms.
• KOL and rebate platforms, such as Based and Phantom wallets, mobile trading platforms, and various social fission rebate KOLs or communities.

In these paradigms, the core investment in prediction markets is too large, and due to political considerations, high valuation prospects for new forces are almost nonexistent. Moreover, tools and rebates tend to cycle with capital inflows and hot topics.

The only worthwhile business investment is in DeFi-ifying prediction assets. Before results are revealed, these betting assets remain in a sedimented state, which might be the most valuable asset in DeFi.

Cross-market arbitrage mechanisms for win-win cooperation

Use Taobao traffic station methods for DeFi, not DeFi methods for DeFi.

Dealing with giants providing traffic services has always been a delicate dance. On one hand, giants need third parties to boost platform traffic; on the other, they do not want third parties to develop brand effects.

This mirrors the early e-commerce traffic station dilemma: they must maintain good relationships with platforms, sellers, and buyers. Sellers need third-party traffic to enhance competitiveness, and buyers want discounts.

Image caption: Third-party services. Image source: @zuoyeweb3

Traffic stations start from rebate perspectives, developing sharing/purchasing/rebate tools. As long as the natural traffic gained by sellers exceeds promotional discounts, the entire business can sustain.

• Sellers rely on platforms for natural traffic; self-branded channels are costly.
• Buyers need platforms for after-sales and rights protection, with payment processes also requiring platform guarantees.

Referring to the “Three Kingdoms” of Taobao—JD—Pinduoduo, the new e-commerce market is overly narrow. The market naturally requires a dual pattern of “brand merchants + long-tail traffic.” New entrants focusing on brand merchants or niche markets cannot achieve scale.

Ultimately, Taobao relies on differentiating Tmall to retain high-end customers, Pinduoduo leverages WeChat to surround the world from rural China, while JD, focusing on brands, struggles to advance or retreat.

Comparing this to the rebate mechanism of exchanges: rebate KOLs and exchanges seek to increase retail investor followings, but retail profits or losses do not affect the order-following mechanism. This differs from e-commerce rebates, where users’ initial purchase needs make discounts beneficial for traffic and seller promotion.

From this perspective, Hyperliquid and Polymarket’s builder mechanisms do not solve the above issues; their growth is solely driven by increasing trading volume.

This is not to say that increasing volume is unimportant, but it still results in capital sedimentation. More volume means more sedimented funds, which is undesirable for the capital-efficient financial industry.

If one cannot break free from the growth logic of CEX/DEX, prediction markets will quickly reach a peak because the number of public events available for trading is limited. Smaller, more instantaneous events tend to favor whales, leading to a real move toward exchange tracks.

Information game dynamics are the essence of prediction markets. Funds sediment during the process from betting to expiration. How to “utilize” this sedimented capital is the underlying driver for prediction markets and DeFi to move forward together.

Image caption: Leverage prediction assets. Image source: @zuoyeweb3

Do not attempt to interfere with users’ normal betting experience. Currently, discussions on leveraging prediction markets mainly fall into two trends:

1. Gondor’s flow interception, which involves users depositing their positions into DeFi staking after betting, regardless of liquidity management or APY calculations. Simply changing users’ intentions doubles the difficulty and risks leading to high-yield, high-risk accumulation.
2. Kaleb Rasmussen from Messari attempts to price the “Jump Risk” of prediction market prices. As mentioned, prediction market prices can instantaneously jump to 1 or 0. His mathematical reasoning is excellent, but practical financial engineering implementation is very challenging.

Based on current practices, I boldly propose a simpler method to achieve transparent DeFi leverage without disrupting user experience: a cross-market arbitrage mechanism similar to Taobao’s, arbitraging between prediction market audiences and DeFi audiences.

1. The platform provides prediction market order placement services, allowing users to place 0 or 1 positions at discounted prices, obtaining better market prices; the platform gains lower financing costs; prediction markets like Polymarket gain more traffic.
2. The platform or prediction market LP/MM acts as the treasury manager, with users depositing into a protocol treasury cooperating with the prediction market, such as Morpho, earning DeFi stacking yields.

In this process, user betting experience remains unaffected. As long as the platform’s discounted cost is less than the DeFi stacking yield, scale effects will emerge. Users will ultimately face their own profit or loss, but unlike rebate mechanisms, they place orders based on their judgment.

Unlike the infinite issuance of xUSD that triggers leverage, Polymarket’s USDC exists genuinely. The only risk is the operator’s skill.

• Prediction market platform: Embeds into broader DeFi stacks, increasing platform trading volume without harming user experience.
• Operator + LP/MM: Utilize sedimented funds, and funds with fixed maturity can build new models beyond short-term arbitrage.

Similar to rebate systems of third-party traffic stations, buyers still generate transaction relationships with platforms and sellers. Prediction market bettors (Yes/No) also trade with Polymarket, unrelated to treasury operators.

Moreover, Polymarket remains at the core of the entire trading process, benefiting from Morpho’s open architecture. Even if bad debts occur, normal liquidation processes are followed, minimizing platform liability.

Conclusion

Use DeFi thinking to “harvest” traffic benefits, not traffic thinking to buy DeFi volume!

The true value of prediction markets lies in capital sedimentation, with clear expiration dates and corresponding asset reserves. If Polymarket wants to outperform Kalshi in capital efficiency, its scale expansion has already reached a stage limit.

In other words, compared to trading assets, Wall Street and the crypto world are in an irrational frenzy over information pricing. Whether it’s TGE, IPO, stablecoins issuance, or building L1/L2 chains, these are routine actions within expectations.

Before uncertain date TGE/IPO, Polymarket needs to strengthen its surrounding ecosystem to boost trading volume and counter Kalshi. The programmability and composability of on-chain funds are the solutions for external traffic for Polymarket.

The biggest financial opportunities in 2026 will be the mid-term elections and World Cup, with FIFA courting China, regulators easing DeFi and gambling, making it a truly prosperous year for finance.