On February 14, 2026, East 8 Time, Vitalik Buterin posted on social media, pointing out that the current chain-based prediction markets' over-reliance on short-term games and the pattern of losses from “naive traders” is “unhealthy,” and proposed a reconstruction vision centered on “broad hedging.” This statement directly addresses the current reality: many mainstream prediction protocols have highly concentrated trading volumes in short-term cryptocurrency prices and sports betting, where participants repeatedly enter amid high dopamine stimulation and are repeatedly harvested in high volatility and information asymmetry. Thus, a new conflict has come to light—how can speculative play focused on excitement coexist with and even reconstruct long-term risk management tools as financial infrastructure? The core question Vitalik raises is provocative: do prediction markets have the opportunity to turn away from the casino narrative of “harvesting naive retail investors” and instead evolve into a risk moat that provides real hedging services for individuals and institutions?
From Casino to Safe Haven: The Narrative Tear of Prediction Markets
● From a public impression perspective, prediction markets have long been viewed as a gambling tool disguised as an “information market,” whether it is on political elections or sports events, they are seen as closer to bookmakers rather than serious financial instruments in the public discourse of most jurisdictions. This image directly invites regulatory sensitivity: some jurisdictions ban and crack down on prediction protocols, not due to the underlying technology, but because they are seen as circumventing licensing requirements for cross-border online gambling, which made the “casino narrative” overshadow any innovative imaginative space in the early stages.
● Vitalik's critique this time targets the ethical and sustainability issues behind this model—he bluntly stated that relying on “naive traders” continuously losing to sustain platform income is an unsustainable and unhealthy business structure. In the long run, this model encourages project teams to design more exciting and complex gameplay to increase rookie error rates and stop-loss thresholds, which in turn suppresses the effectiveness of information and the price discovery function, making prediction markets drift further away from their original intention of “aggregating cognition through prices.”
● Currently, the mainstream prediction markets on-chain are highly concentrated in two types of high-frequency bets: firstly, short-term cryptocurrency prices that span a few hours to a few days, simplifying complex macro and on-chain behavior into a binary choice of “up/down”; secondly, sports betting, represented by large events, which is inherently driven by emotion and preference. The common characteristics of both are short result cycles, fast odds feedback, and simple narratives, which easily amplify speculative attributes but rarely have direct links to the long-term risk exposures faced by participants in the real world.
● For institutions and compliant funds, this “casino-style” structure almost naturally forms a barrier. On the one hand, compliant asset managers require tools that are auditable, explainable, and highly aligned with real risk management goals rather than income derived from zero-sum games of counterparty losses; on the other hand, the high-pressure regulatory stance on gambling and unregistered securities makes direct participation in such markets very costly in terms of compliance and reputation. Therefore, although prediction markets are technically open and unlicensed, a foundational structure capable of accommodating large-scale institutional liquidity has yet to be established.
The Blueprint for Broad Hedging: Making Every Future Insurable
● In this announcement, Vitalik proposed the vision of “broad hedging”: no longer limiting prediction markets to a game of betting on whether an event occurs, but understanding it as a universal risk management layer. Individuals and institutions can buy and sell contracts targeting different future scenarios to hedge against fluctuations in income, costs, asset prices, etc., allowing “future possibilities” to be split, priced, and embedded on-chain in the form of contracts.
● From the evolution context of DeFi infrastructure, this idea is not abrupt. In recent years, the market has built a programmable financial framework using mainstream assets such as ETH in lending, DEX, derivatives, and other sectors. Vitalik's concept is to further use assets like ETH as underlying collateral to support a decentralized risk hedging network, where different types of risk exposures can be expressed, traded, and settled with standardized contracts, forming a public layer of “hedging as a service.”
● In more practical scenarios, this means individuals and businesses can customize protection around variables they genuinely care about. For instance, individuals highly dependent on a specific industry’s prosperity can buy contracts for “deterioration in unemployment rate” or “downward trends in the industry index” to obtain partial compensation during economic downturns; businesses can design corresponding compensation structures around commodity prices, logistics costs, or exchange rate fluctuations, bringing traditional financial hedging strategies that have high entry barriers down to a more granular level and more open approach within the on-chain environment.
● Implicit in this is a paradigm shift: from designing products around “bets,” to designing contracts around “real risk exposure.” In the former model, product teams think first about what events are more stimulating and easier to attract traffic and fees; in the latter model, the starting point shifts to identifying under what future scenarios users would face significant losses, and providing transparent, priceable, and combinable hedging tools for those scenarios. If prediction markets evolve along the latter path, their valuation logic could shift from an entertainment and traffic platform to a long-term cash flow perspective similar to infrastructure and insurance layers.
ETF Bloodletting and Fund Anxiety: The Pricing Void Behind the Barometer
● According to data from a single source, this week the US Ethereum spot ETF saw a net outflow of about $161.2 million, while the Bitcoin spot ETF experienced a net outflow of about $360 million in the same period, indicating a general contraction attitude from institutions and compliant funds toward current cryptocurrency asset allocations. As a product that has been seen over the past two years as a symbol of “formal military entry,” this continuous bleeding itself has become an important barometer for market sentiment.
● The outflow of funds at the ETF level is often interpreted as rising risk-aversion sentiment and the accumulation of uncertainty regarding future paths of spot prices. On one hand, the opacity of the macro environment and regulatory expectations causes some institutions to choose to reduce holdings of high-volatility assets; on the other hand, in the absence of effective hedging means, simple position reduction often becomes the most direct and crude form of risk management. This “voting with feet” behavior reinforces market expectations of mid-to-short-term price pressure, forming a self-reinforcing negative feedback loop.
● In the traditional financial toolbox, hedge products around stocks, interest rates, exchange rates, and commodities are highly mature, but when the underlying becomes on-chain assets, the existing system's offerings are quite limited. Whether futures, options, or structured notes, their coverage, liquidity, and availability are insufficient to serve the broader risks of cryptocurrency assets and on-chain activities, let alone provide inclusive risk management capabilities for small and medium-sized entities and individuals, which is especially stark in the context of continuous outflows from ETFs.
● The tensions formed as a result are very distinct: funds are retreating to protect themselves while, on the other hand, the underlying infrastructure that can structure and manage crypto risks has yet to take shape. The “broad hedging” layer that Vitalik envisions precisely targets this gap—if on-chain native hedging protocols can be generated deeply tied to cryptocurrency assets, then when the next macro uncertainty arises, institutions and individuals may not have to resort to “complete withdrawal” to combat black swans but can maintain some participation rights for the future through more refined contract configurations.
The Next Piece of the DeFi Puzzle: Hedging as a Service and the Liquidity Paradox
● Looking at prediction markets in the evolution sequence of DeFi, they resemble a delayed puzzle piece. From the initial lending protocols solving on-chain interest and collateral needs, to DEX facilitating spot liquidity, to derivatives protocols expanding leverage and hedging possibilities, the next natural question is how to package these capabilities as “hedging as a service.” If prediction markets can be restructured with the goal of risk management, they will have the opportunity to become a universal risk interface connecting individuals, businesses, and the protocols themselves.
● Regarding pricing mechanisms, decentralized price indices and AI models may play a more important role in the future: the former provides credible on-chain reference prices for different assets and risk factors, while the latter helps abstract more representative contract objects from massive data when building composite indices and risk baskets. However, there remains significant uncertainty regarding the technical paths for specifically implementing local AI modeling and maintaining complex indices efficiently on-chain; related details need to be validated in more complete technical literature and implementation plans.
● The conflicts at the commercial model level are equally sharp: today, much of the income from many prediction protocols comes from the information and cognitive gaps between “naive traders” and more seasoned participants, while Vitalik’s envisioned world relies more on charging hedging service fees, facilitating professional market makers to earn spreads and liquidity subsidies to sustain operations instead. Although the latter may result in lower profit margins per user, it excels in sustainability, complies with larger flexibility, and aligns better with the narratives of “infrastructure” and “moat.”
● However, any broad hedging market aiming for profundity cannot bypass the issues of liquidity and counterparties. Without enough, sufficiently professional hedging demand parties presenting clear, priceable risk exposures, and without willing market makers providing continuous quotes for long-term presence, even the most sophisticated contract designs can only remain in white papers. How to attract genuinely risk management-needing users in the early stages through incentive mechanisms, rather than merely chasing airdrop sheep, will determine whether this puzzle piece can be successfully integrated into the DeFi landscape.
Fiat Currency Replacement or Regulatory Red Line: The New Identity Struggle of Prediction Markets
● From a legal domain perspective, the legal classification of prediction markets has long been highly fragmented: in some countries, they are directly equated with gambling and require gambling licenses; in other jurisdictions, they are treated similarly to derivatives or securities needing to comply with stricter financial regulations; and in a few scenarios, they are described as “information markets” and receive exemptions in small-scale, academic, or experimental settings. This label fragmentation itself constitutes a significant barrier for projects and participants in cross-border operations and compliance design.
● As prediction markets begin to take on functions of “informal insurance” or “shadow derivatives,” a more sensitive issue has arisen: are they quietly becoming a complement to the fiat financial system, or even replacing it in certain marginal scenarios? If individuals and businesses can use decentralized prediction contracts on-chain to complete some risk management tasks originally undertaken by banks, brokerages, or insurance companies, then traditional financial institutions and regulators will inevitably reassess the position of these protocols within the overall framework of currency and financial stability.
● In the regulatory gray areas, the tension between anonymous on-chain hedging and KYC platform services is particularly pronounced. The former emphasizes permissionless, censorship-resistant, and globally accessible, yet may be seen by regulators as an evasion of regulation, the “black box”; the latter attempts to provide prediction and hedging services within a compliant framework, exchanging legal identities for real-name systems and regional restrictions, but has also sacrificed some degree of openness and censorship resistance. Different jurisdictions may adopt entirely different strategies along this spectrum, ranging from complete prohibition to sandbox pilot programs, with highly varying paths.
● For the prediction markets envisioned by Vitalik to gain survival space in reality, they must find gaps in this compliance game: on the one hand, avoiding being simply and crudely categorized as gambling or illegal derivatives leading to comprehensive crackdowns; on the other hand, accepting a certain degree of rule embedding without straying too far from the spirit of decentralization. This may mean starting with a narrative core centered on serving genuine risk management needs, reducing “casino feel” through transparent fees and risk disclosures, and proactively connecting with traditional financial infrastructures rather than opposing them.
From High-Frequency Pleasure to Slow Variable Moat: Who Pays for the Future?
● Overall, the “broad hedging” vision proposed by Vitalik is essentially trying to rewrite the storyline of prediction markets: shifting from a casino driven mainly by high-frequency pleasure and emotional release to a risk infrastructure embedded in the balance sheets of individuals and institutions. If this narrative holds, the valuation logic of prediction protocols, the structure of participants, and regulatory attitudes may fundamentally change, becoming one of the important pillars in the mature stage of DeFi.
● However, to achieve that, the real-world resistance is equally clear: regulatory uncertainties determine that many bold product forms cannot easily take shape; the technical realization details—including how to efficiently price complex risks, how to maintain multi-dimensional indices on-chain, and how to ensure settlement safety under extreme market conditions—are still far from finalized; more critically, whether genuine hedging demand is concentrated enough and willing to pay has yet to be sufficiently validated, which decides whether “hedging as a service” can move from whitepapers to balance sheets.
● From the perspective of the game, retail investors, institutions, and regulators will make their respective choices on the axis of “speculation vs. risk management.” Will retail investors be willing to transition from more stimulating short-term bets to contracts that offer slower returns but are closer to real-life risks? Are institutions willing to bear the technical and compliance risks of early adoption in exchange for first-mover advantages in new risk infrastructures? Will regulators see these tools as a new safety valve for buffering financial shocks rather than purely a breeding ground for speculation? These choices will collectively shape the next face of prediction markets.
● In the coming years, certain observable indicators may help us judge the trend: will prediction protocols emerge that focus on “risk hedging” instead of “odds and pleasure” as core narratives; will more compliant-friendly product forms gain access in multiple jurisdictions; and will institutional funds start using such tools systematically for hedging rather than purely allocating purposes? If these signals gradually become clear, prediction markets may indeed have the opportunity to evolve from a passive casino that simply absorbs emotions to a risk infrastructure layer that builds moats around slow variables.
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