Vitalik Buterin warns prediction markets risk becoming speculative “corposlop,” urging a shift toward hedging and long-term financial utility.
Vitalik Buterin, co-founder of Ethereum, shared insights and warnings around the long-term sustainability of prediction markets. He argued in a recent X post that the sector may be drifting toward short-term speculative products at the expense of broader financial utility.
Buterin acknowledged that prediction markets have reached meaningful scale, with enough liquidity to support professional traders and serve as a supplementary information layer to traditional media. But he warned that the dominant growth categories, short-term crypto price bets and sports contracts, are short-sighted.
“They seem to be over-converging to an unhealthy product market fit: embracing short-term cryptocurrency price bets, sports betting, and other similar things that have dopamine value but not any kind of long-term fulfillment or societal information value,” Buterin wrote.
His concern is not that sports betting or price speculation are inherently flawed. Rather, he suggests that platforms are optimizing for what generates revenue in difficult market conditions. But at what expense?
The sustainability question beneath the surface
Buterin posed a structural question around prediction markets: who consistently loses money, and why would they return?
Every market needs both informed traders and counterparties. In the current model, a large portion of volume appears to come from retail participants expressing directional views on sports, elections, or crypto prices. As liquidity increases and institutional market makers tighten spreads, the edge tilts toward sophisticated participants.
That dynamic has caused criticism from some observers. In response to well-known professional trader Domer’s endorsement of Buterin’s post, one X user argued prediction markets are “unlikely to ever be beneficial to society” and will primarily function as a wealth transfer from the naive to those with superior information.
The critique indicates a genuine tension. If markets are dominated by sharp traders and professional liquidity providers, casual participants may struggle to win often enough to justify continued engagement. Traditional sportsbooks manage this tension through entertainment, bonuses, and parlay mechanics. Prediction markets, by contrast, often market themselves as information discovery tools.
The sector’s growth over the past two years has been mainly due to sports markets expansion and crypto price volatility. Those categories are simple to understand and naturally generate recurring demand. But if the ecosystem’s health depends on a constant influx of less-informed capital, the long-term sustainability becomes fragile.
Hedging as a structural alternative
Buterin’s alternative vision is to push prediction markets toward generalized hedging rather than entertainment speculation.
He argues that markets can serve as insurance-like instruments. For example, an investor with exposure to biotech equities could hedge political risk by taking a position against the outcome that would negatively impact the sector. Even if the trade carries a slight negative expected value, the reduction in portfolio volatility has real utility. Kalshi has been making moves to become a hedging vehicle in the sports business (and betting) industry.
Under this model, the consistent loser is not naive capital but rational actors paying for risk transfer. That establishes prediction markets as financial infrastructure.
Domer, a trader who made $3M+ trading on Polymarket echoed this perspective, writing that there is “a level of short term thinking” that treats current markets as disposable gambling products, when the long-term opportunity “can be a lot bigger, more complex, and beneficial to society.”
The implication is that sports-driven growth may represent only the first phase of adoption, not the final form.
“Really good post. There is a level of short term thinking/strategizing/marketing that treats these markets as disposable, small potatoes gambling compared to the total opportunity. Which can be a lot bigger, more complex, and beneficial to society.”
Liquidity providers and ecosystem design
For this structural transition to occur, liquidity design becomes important.
Professional firms increasingly provide depth on regulated venues. Their participation compresses spreads and improves execution quality, but it also intensifies competition. If markets become too efficient too quickly, retail participants lose informational edge, and churn increases.
At the same time, institutional hedgers will not participate without big liquidity and reliable settlement. That creates a circular dependency: deeper liquidity attracts hedgers, hedgers stabilize demand, and stable demand sustains liquidity. The challenge is balancing these forces without allowing the ecosystem to tilt entirely toward entertainment speculation or exclusively toward professional arbitrage.
Prediction markets are still early in this lifecycle. Unlike equities or options markets, they lack decades of surveillance frameworks, standardized clearing systems, and big institutional mandates. That immaturity makes sports and crypto price contracts the easiest path to volume.
But ease does not necessarily equate to durability.
The risk of over-optimization
The sector’s fast expansion has been accompanied by parlay-style products, short-duration contracts, and leveraged structures designed to increase engagement. These features boost turnover and revenue but also increase the perception that prediction markets are simply sportsbooks with different rails.
If public perception solidifies around that, the expectation that prediction markets can become foundational risk-transfer infrastructure becomes harder to execute.
Buterin’s argument is ultimately about incentives. Platforms that rely heavily on speculative retail flows have an incentive to create high-volatility, high-dopamine markets. Platforms that cultivate hedgers and institutional participants have an incentive to invest in reliability, clarity, and settlement integrity.
Both models can coexist, but their long-term trajectories differ.
