The Price of Truth - ForkLog: cryptocurrencies, AI, singularity, the future

# Price of Truth

How Prediction Markets Operate in an Era of Uncertainty

In 2025, prediction markets experienced a real boom, driven by advances in regulation and growing interest from the broader public. From enthusiast tools, they are transforming into a full-fledged industry with the potential to surpass a trillion dollars by the end of the decade.

From the early, mysterious days of Bitcoin’s emergence to the DeFi boom that reshaped the financial landscape, prediction markets remain one of the few innovations where the human factor is especially prominent. In their basic form, they turn expectations about future events into tradable prices: for example, a contract trading at $0.60 indicates that the market estimates about a 60% probability of the outcome.

Proponents of such platforms argue that because participants risk their own funds, prediction markets reflect the collective information more quickly than traditional polls. Critics, however, often compare them to gambling—especially when it comes to sporting events. Regardless of who is right, it is unlikely an exaggeration to say that prediction markets are no longer just forecasting the future. Rather, they are prompting us to rethink how we define truth in the post-truth era, appealing to the deep human desire to find order in chaos.

From Ancient Oracles to Modern Financial Markets

The idea of predicting the future in various forms has existed since antiquity. In Ancient Greece and Rome, oracles interpreted omens to make political or military decisions, effectively serving as the first institutional forecasting systems.

Similar practices developed in other cultures, though they were far from the modern concept of a “market.” In China, the I Ching ( or “Book of Changes” ) offered a structured divination system where the questioner formed a hexagram—often using stalks of yarrow or coin tosses—and interpreted it as guidance for decision-making. In Babylon, scholars observed planetary movements, stars, and eclipses, providing rulers with advice on war, harvests, and other matters based on these observations. Meanwhile, the Maya used complex calendar systems to determine “favorable” and “dangerous” periods, aligning ceremonies, governance, and agriculture with cyclical time.

By the 16th century, in certain regions of Europe—primarily Rome during papal conclaves and Venice—informal bets on political outcomes with high stakes became common. Essentially, they turned collective expectations into odds backed by real money, serving as conceptual precursors to modern prediction markets.

In the 20th century, political betting pools in the US, monitored by financial publications, often proved more accurate than traditional polls. One of the most frequently cited examples of their effectiveness is the Iowa Electronic Markets (IEM), which have been repeatedly compared to classical sociology in academic research. Peer-reviewed analyses of electoral markets like IEM showed that their forecasts were generally closer to actual results than sociological polls conducted during the same periods across multiple presidential cycles.

However, commercial platforms faced rapid regulatory restrictions. For example, in 2012, Irish Intrade was shut down for US users under pressure from the Commodity Futures Trading Commission (CFTC), and the platform ceased operations entirely the following year. PredictIt, which operated for a long time under a no-action letter from the CFTC (no-action letter), faced serious issues in 2022 when regulators ordered its closure. Later, the company won a court case against the CFTC and continues to operate.

These centralized platforms contributed to the development of prediction market concepts but also demonstrated their dependence on legal frameworks and operational restrictions.

Emergence of Blockchain Prediction Markets

The integration of blockchain into prediction markets began around 2014–2017, relying on smart contracts for automated and decentralized operation. Augur was one of the first such projects: after a lengthy beta period, it launched in 2018 using its own token REP.

However, the platform faced several issues—high Ethereum network fees, unstable node operation, and an inconvenient interface requiring users to run full nodes. The second version was launched in July 2020, offering improvements in speed and functionality.

Augur became one of the first projects to implement decentralized oracles, allowing users to ask questions about the future without trusted intermediaries. Yet, it also faced problems, including fraud and lower adoption compared to centralized competitors.

Currently, Augur is in a reboot phase: in 2025, the Lituus Foundation launched an initiative to revive the platform, aiming to adapt it to the modern crypto industry. The project focuses on restoring infrastructure, enhancing oracle security, and improving user experience after a long period of stagnation.

Gnosis launched in 2015, largely echoing Augur’s vision of prediction markets. In April 2017, it successfully conducted an ICO, raising $12.5 million in ETH. Projects like the decentralized cross-chain prediction market Omen operated on Gnosis. Over time, the team shifted focus away from end-user markets—main reasons cited include an inconvenient interface, limited financial resources, and regulatory uncertainty.

In response to rising market demand, Gnosis shifted toward building infrastructure solutions for the Ethereum network. These include the Safe platform for managing digital assets, the open protocol for DEX liquidity aggregation CoW Protocol, and the Conditional Tokens Framework—a framework for issuing and trading tokenized outcomes of events.

In 2020, GnosisDAO was created to manage the ecosystem, emphasizing payment solutions and oracles. This cemented Gnosis’s role as an infrastructure provider for modern platforms, including Polymarket.

Alongside Augur and Gnosis, other decentralized prediction markets have emerged, utilizing blockchain to forecast events without intermediaries. Notable among them is Zeitgeist—a protocol focused on cross-chain scalability and secure market operation based on Substrate. Zeitgeist functions as a standalone parachain within the Polkadot/Kusama ecosystem, enabling the launch of markets and on-chain trading of tokenized event outcomes, using the ZTG token as the basis for incentive mechanisms and network governance.

The project also experiments with futarchy—a governance model popularized by economist Robin Hanson, which involves “voting on values but betting on beliefs.” A dedicated futarchy module is integrated into the platform’s architecture. When outcomes are disputed, the Zeitgeist “decentralized court” acts as the final arbiter—ZTG token holders can participate in dispute resolution through a staking mechanism.

Current State of Prediction Markets

By 2025, prediction markets have moved beyond a niche fintech segment to form a recognizable category of event-driven finance. Liquidity on these markets has significantly increased, and access has shifted from specialized platforms to mass brokerage and consumer applications. The level of activity indicates the segment’s maturity: according to industry research, from January to October 2025, the total trading volume on prediction market platforms exceeded $27.9 billion (in terms of traded contracts), with weekly trading reaching a historic high of about $2.3 billion since October 20, 2025.

However, estimates that include a different set of platforms and use alternative methodologies report a higher trading volume for 2025—around $44 billion. This clearly demonstrates how heavily the final figures depend on the calculation method.

Regulated “Event Contracts” and Crypto-native Platforms

Today, the market is increasingly divided into two directions: on one side, the spread of “event contracts” in the US under CFTC oversight; on the other, crypto-native prediction markets operating on on-chain settlements and oracle systems. In the regulated segment, Kalshi continues to strengthen its position as a leading US platform, valued at around $11 billion. It leveraged its regulatory status to scale its products and attract capital. One of the key goals for the company in the coming year is to integrate its platform into major blockchain applications and exchanges.

Meanwhile, channels through which prediction markets are accessible to the mass public have expanded. In March 2025, Robinhood launched a dedicated prediction markets section, later strengthening its presence by introducing its own futures and derivatives exchange, as well as clearing infrastructure.

On the side of native crypto platforms, Polymarket remains the most recognizable brand for the general user. It benefits from low fees and a familiar trading interface, while utilizing crypto infrastructure for settlements. Its oracle system is closely linked to UMA’s Optimistic Oracle, and to reduce fees and support a hybrid order book model, it employs Gnosis framework on Polygon.

A notable institutional signal came in October 2025, when Intercontinental Exchange (ICE), owner of the New York Stock Exchange (NYSE), announced a strategic investment in Polymarket of up to $2 billion, implying a market valuation of approximately $8 billion.

Earlier, Polymarket announced the acquisition of QCEX—a CFTC-licensed exchange and clearinghouse. The deal, valued at $112 million, was described as “laying the foundation for Polymarket’s return home,” meaning re-entering the US market as a fully regulated and compliant platform.

On December 20, Polymarket set a record for daily trading volume in 2025: reaching $188.6 million, comparable to peak levels during the US presidential elections a year earlier.

Mass Adoption and Regulatory Pressure

The last two months of 2025 in the sector were marked less by technological breakthroughs than by a series of rapidly concluded deals and simultaneous increases in regulatory pressure. For example, Kalshi and Crypto.com initiated the formation of a nationwide coalition of prediction market operators in the US. The coalition, which also includes Coinbase and Robinhood, aims to coordinate the industry’s public stance amid growing regulatory attention.

At the same time, Coinbase deepened its involvement in the event contract segment: in mid-December, the company announced plans to launch prediction markets directly within its main app in partnership with Kalshi, as well as a deal with startup The Clearing Company.

Traditional betting companies and exchange infrastructure also entered the prediction market segment. FanDuel, together with CME Group, launched the FanDuel Predicts product in five states, with plans to expand in 2026. Meanwhile, DraftKings introduced DraftKings Predictions—a standalone mobile and web product allowing trading of contracts tied to real-world outcomes across various markets. The launch started with sports and finance, with plans to add entertainment and cultural sectors later.

However, problems quickly arose. In early December, the Connecticut Department of Consumer Protection accused several platforms, including Kalshi and Crypto.com, of organizing unlicensed betting, equating sports predictions with gambling. In response, Kalshi filed a lawsuit in federal court and obtained a temporary restraining order against the ban—hearings are scheduled for early 2026.

Nevertheless, this case is another indication that the boundary between state gambling laws and federally regulated event contracts remains blurred.

Additional uncertainty stems from tax issues. Coinbase Institutional analysts note that in the US, taxes may be calculated differently for regular sports bets and for trading event contracts. This shows that the popularity of such products is growing faster than clear and uniform rules are being established.

The situation is further complicated by a new tax and budget package, also known as the One Big Beautiful Bill Act*: starting in 2026, it will limit the ability to deduct losses for tax purposes. According to analysts, as a result, blockchain prediction markets could become a more tax-efficient alternative to traditional bookmakers for some users.

Challenges and Development Prospects

With support from giants like Intercontinental Exchange and increasing institutional involvement, the prediction market industry enters 2026 with substantial resilience. But at the same time—no less uncertainty. Depending on how regulatory issues are resolved, these markets could either become full-fledged financial products or fragment into separate segments with different rules.

Much likely depends on three factors:

• where exactly regulators and courts draw the line between gambling and legitimate hedging or market price discovery tools; whether state and federal regulators can agree on clear jurisdiction boundaries;
• whether institutional partners—exchanges, brokers, and market makers—will continue supporting liquidity growth beyond short-term spikes, such as during elections.

According to Eilers & Krejcik, trading volume on prediction platforms could reach $100 billion in 2026, and by the end of the decade—exceed $1 trillion. Meanwhile, co-founder of TradeFox AI, Yoshish, believes that growth will follow a consolidation path: only a few major platforms like Polymarket and Kalshi will remain, where most liquidity will be concentrated.

From the crypto-native side, the next growth phase will likely unfold on-chain—where calculations are automated, and markets can be directly integrated into DeFi infrastructure. If this scenario materializes, the next wave will probably involve deeper integration with decentralized finance, the use of oracles with AI elements, and experiments with governance—such as futarchy in projects like MetaDAO, where markets not only predict events but also help in decision-making. In such a case, platforms could evolve into programmable “truth engines” on a global scale.

In this model, Ethereum and its Layer 2 networks are likely to remain the main hubs of liquidity—thanks to deep capital pools and established infrastructure. Solana will continue attracting fast, user-oriented markets where speed and low fees are critical. Ultimately, a dual-layer on-chain ecosystem may emerge, with some networks optimized for liquidity and complex financial structures, and others for rapid price discovery and active trading.