Forecasted Market Daily Trading Volume Soars 7 Times! 2030 Trillion USD Market Arbitrage Strategy

Forecasted market daily trading volume surges from 20 million USD in September to 20 billion USD in October, a 7-fold increase. Institutions predict that by 2030, the scale will reach trillions of dollars, with the 2026 World Cup serving as a catalyst. This track is fundamentally different from traditional crypto trading: it ignores K-line charts and focuses solely on probabilities; it tells no stories, only facts. Smart money is realizing recognition monetization through arbitrage strategies.

The Three Main Logic Pillars of Recognition Monetization by Smart Money

The core appeal of prediction markets isn’t technological innovation but their redefinition of the underlying logic of “value capture.” In traditional crypto markets, capital is the greatest advantage, but in prediction markets, information, cognition, and speed are the winning weapons. Behind the stories of huge profits made by smart money, there are three clear paths of recognition monetization.

The first path is the time window of mathematical arbitrage. When the YES probability of an event on Polymarket is 55%, and the NO probability on Kalshi is 40%, the total probability is only 95%, leaving a 5% riskless arbitrage opportunity. The key is speed: whoever’s script scans for such imbalances faster can place orders first. French trader Théo discovered hidden voter tendencies through “neighbor effects” during the 2024 US election, reversing positions when odds are unfavorable, ultimately earning tens of millions of dollars. His advantage isn’t insider information but an exclusive research methodology.

The second path is AI-driven information gap models. Machines read much faster than humans; when major news is released, AI can analyze content and predict market changes within milliseconds. For example, before the Federal Reserve rate decision, market consensus had reached 99%, but prediction market prices still hovered around 0.95 or 0.96 due to capital costs—this is the “interest of time.” Large funds treat high-certainty events as short-term bonds, earning certain yields. The core of this strategy is pricing uncertainty as bond yields, not betting odds.

The third path involves the gray area of oracle manipulation. In July 2025, regarding the event “Zelensky wearing a suit before July,” media reports indicated Zelensky had worn a suit, but in UMA votes, four large holders with over 40% of tokens voted “NO,” causing counterpart users to lose about 2 million USD. This exposes a fatal weakness of prediction markets: letting UMA tokens, with a market cap under 100 million USD, serve as judges for markets like Polymarket is a structural risk.

Risks and Traps in Polymarket Arbitrage Strategies

Pure mathematical arbitrage judgment traps: Different platforms may have different criteria for the same event. During the US government shutdown in 2024, Polymarket judged “shutdown occurred” (YES), while Kalshi judged “shutdown did not occur” (NO). The reason is Polymarket’s settlement standard is “OPM issued shutdown announcement,” whereas Kalshi requires “actual shutdown lasting over 24 hours.” Arbitrageurs lose on both sides.

Initial liquidity sniping arms race: When a new market opens, the first orderer has absolute pricing power. But this requires hosting servers very close to the nodes to reduce latency, similar to high-frequency trading arms races like MEME sniping. Once speed advantages disappear, one becomes the taker.

Causal failure in related market arbitrage: There is a causal chain between “Trump winning the election” and “Republicans winning the Senate,” but the correlation between “Messi missing a match” and “team losing” may fail. This strategy requires a deep understanding of the underlying logic of political or sports events, not just simple correlation inference.

On-chain reverse harvesting of follow trades: Monitoring high-probability addresses and following whales’ positions sounds safe, but whales may be hedging or deliberately releasing false signals. Cases in 2025 show that some “smart money addresses” are actually multi-signature wallets’ test orders or risk hedging positions, and followers are ultimately reverse harvested.

All these strategies rely on asymmetric information, technology, or capital advantages, but such advantages are only effective during market immaturity. As secrets are exposed and markets mature, most arbitrage opportunities will quickly disappear, similar to early crypto cross-exchange arbitrage.

Imagining 2030 Trillion USD and Stress Testing in 2026

Currently, prediction markets have only accumulated 38.5 billion USD in trading volume, less than a single day’s trading volume on Binance, with an average of 200 million USD daily, ranking around 50th globally. But institutions forecast that by 2030, annual trading volume could reach 1 trillion USD, representing over 50 times growth.

The 2026 World Cup is seen as a key catalyst and stress test. Sports events have three characteristics: dense events, clear outcomes, and global attention. During the World Cup, prediction markets could face daily trading volumes in the billions of USD, testing liquidity depth, settlement speed, and oracle reliability. If it passes the stress test smoothly, institutional funds and mainstream users will flood in. If large-scale manipulation or settlement disputes occur, it could trigger a crisis of trust.

The fundamental value of prediction markets lies in solving the “cost of truth” problem. In an era of rampant fake news, traditional market research or expert forecasts lack credibility, while prediction markets realize collective intelligence through “real money voting.” More importantly, they directly convert individual expertise or information advantages into money, which is fundamentally different from traditional finance and crypto markets: capital is no longer the greatest advantage; technology and cognition are.

However, prediction markets also face issues such as short market cycles, low liquidity in niche markets, insider manipulation risks, and regulatory challenges. The most critical question is: when the narrative vacuum period in crypto markets ends, can prediction markets maintain independent trends? This will determine whether they are a fleeting hotspot or a truly trillion-dollar track.