Paradigm designs a new type of prediction market: can you bet without an opposing side?

Authors: Dave White, Matt Liston

Translation: Luffy, Foresight News

Imagine you discover an unsigned band destined for stardom. Instead of cold-calling a record label, what if you could personally "bet" on them?

The "opportunity market" introduced in this article is precisely such a private prediction market: people who identify opportunities can be rewarded by those with the ability to act.

Record labels, research labs, and venture capital firms all want to find the next big thing before their competitors. But those who first spot an opportunity often lack access to institutional resources. For a long time, these two groups have lacked a seamless way to connect and transact.

Prediction markets extract valuable signals from distributed participants by requiring them to put real stakes at risk. However, if someone wants to earn $1 million betting that "XYZ will become a hit," there must be someone else willing to bet $1 million against it. Yet no one wants to take the opposite side of thousands of obscure "opportunities" they've never heard of.

The natural counterparty for such markets should be entities capable of taking action—such as record labels, employers, or funds. But if they provide liquidity in public prediction markets, they effectively "subsidize" information that competitors can easily exploit.

Opportunity markets solve this problem by revealing market prices only to the sponsor.

A record label might provide up to $25,000 in liquidity for a market like "We will sign artist XYZ in 2025." This "no-lose money" can be claimed by scouts who act early. When the label sees rising prices for a particular market, it treats this as an early signal to investigate the artist further. Prices and positions are only disclosed after an "opportunity window" (e.g., two weeks). It's like a decentralized scouting program where anyone in the world can participate with real skin in the game.

The practical challenge is that traders operate without price or position feedback for extended periods—essentially "blind trading"—and self-trading risks are evident. Still, we believe significant value exists here, and the design space is broad.

Core Concept

Motivation

Imagine a music fan discovers an unsigned artist destined for fame. The fan holds valuable information but lacks connections to record labels; meanwhile, the very label that could sign the artist has no idea they exist. Similarly, suppose a researcher finds a breakthrough related to autonomous driving buried in an obscure paper, yet lacks the resources to commercialize it—while companies investing billions in R&D remain completely unaware of the paper.

This pattern repeats across domains: shop owners spot trends before big brands, local suppliers identify promising startups before investors, fans recognize athletic talent earlier than the general public.

In each case, frontline individuals with deep contextual expertise possess information highly valuable to resource-rich actors who can act upon it. But there's no mechanism connecting them: those with information cannot monetize their insights, while those with resources miss opportunities.

This article focuses specifically on opportunities where evaluation and action require substantial resources and are competitive and time-sensitive—meaning significant advantage comes from knowing about them earlier than other capable actors.

Existing Mechanisms

Scouting programs are one solution to this issue. They offer small revenue shares to specific groups with contextual knowledge for identifying opportunities. But such programs are limited by trust requirements and evaluation costs: institutions cannot scale beyond their capacity to vet scouts and submissions.

Prediction markets are proven tools for aggregating information from broad, dispersed populations. But they face incentive problems: if someone wants to profit handsomely from betting on an artist’s success, someone else must bear the corresponding loss. Market makers have little reason to risk large sums betting against an unknown artist. Even when institutions subsidize market liquidity to gather information, most current prediction markets treat information as a public good—enabling competitors to free-ride on these signals, ultimately eroding any advantage. This is the core "information leakage" problem that opportunity markets aim to solve.

Mechanism Design

Example

An example best illustrates the concept. Suppose a record label wants to use an opportunity market to create a decentralized scouting program.

They create a series of private prediction markets with propositions like "Will we sign artist X in 2025?" Here, X can be any artist. Anyone can create new markets for artists not yet listed and add them to the series.

"Private" means only the sponsor (i.e., the record label) knows the current market price at any time. Challenges around this are discussed below.

The label acts as a market maker, providing up to $25,000 in liquidity per market. They may commit to this level of liquidity or demonstrate it via mechanisms like running an automated market maker within a trusted execution environment (TEE). Scouts can earn this "no-lose money" simply by acting early. As scouts grow confident in a particular opportunity, they buy more shares, pushing the market price upward. When the sponsor (the label) observes rising prices, they take note and investigate, potentially leading to signing the artist. If a signing occurs, shares pay out, and the label effectively pays up to $25,000 in incentives to its decentralized scouts.

Privacy Protection

For opportunity markets to function, only the sponsor must see the current price. If traders could immediately observe their trade outcomes, they could infer market prices through trading activity.

Yet traders eventually need to know their positions. The solution is an "opportunity window" (e.g., two weeks), after which traders learn whether their orders were filled. This gives the sponsor time to investigate promising opportunities before information goes public.

After the window closes, several design options exist: publish all prices and positions publicly; reveal only individual positions to each trader; apply different rules for large vs. small orders; or implement more complex systems allowing "close-out" limit orders before disclosure, or even agent-based trading without revealing current holdings.

Market Design Details

Liquidity Provision

Markets can use either automated market makers or order books. In either case, liquidity may be concentrated in specific ranges. For instance, sponsors might start offering liquidity at a 1% probability threshold (below which information has negligible value) and stop at 30% (above which additional signal value is limited).

Unbounded Markets vs. "Top N" Markets

For most opportunity types (e.g., signing artists), sponsors can only act on a limited number within a given period. Therefore, if traders trust the sponsor to honor payouts, the sponsor needs only commit to settling unlimited markets like "Will we sign artist X in 2025?" while ensuring total liquidity across all markets stays within bounds they can realistically cover—even if many signings occur. For a more permissionless approach, markets can adopt a "top N" structure with full collateralization. For example, a market proposition like "Will XYZ be among our top 10 signed artists in 2025?" would require collateral equal to 10 times the maximum liquidity per market, since only 10 such markets can ever settle.

Preventing Exploitation

Sponsors possess privileged information about both market states and internal processes, creating exploitation risks—for instance, signaling intent to pursue Opportunity X while heavily selling in that market.

This is difficult to address purely through mechanism design and relies heavily on trust and reputation. Ultimately, participants will only engage in a sponsor's markets if the sponsor consistently demonstrates fairness over time. Sponsors can follow these guidelines:

• Pledge never to actively sell shares in any market they initiate;

• Pledge to return all profits from opportunity market trading either to participating traders or toward funding future market liquidity.

Running opportunity markets inside a trusted execution environment (TEE) and publishing all trades after settlement can also provide transparency and reduce risks.