The Expanding Applications of Prediction Markets—From Macro Events to On-Chain Behavior

I. What Scenarios Are Prediction Markets “Disrupting”?

While the first two lessons explained how prediction markets operate and the third covered secure settlement, the central question for Lesson 4 is straightforward: What are prediction markets being used to predict?

By 2024–2025, prediction markets have clearly evolved beyond early political betting or entertainment purposes. They’re now extending into macro finance, industry events, and on-chain behavior forecasting—emerging as a new tool for pricing information.

Unlike traditional financial products, prediction markets don’t rely on historical data modeling. Instead, they directly aggregate participants’ judgments about the future. This gives them a unique edge in scenarios involving “black swan events,” “discontinuous risks,” and “gray rhino problems.”

II. Macro and Political Events: The Most Established Testing Ground for Prediction Markets

1. Why Are Macro Events Naturally Suited to Prediction Markets?

Macro and political events share several key characteristics:

• Clear outcomes (election results, policy approval)
• Significant impact but difficult to quantify
• Large errors in traditional polling and expert forecasts

Prediction markets use price mechanisms to condense scattered subjective opinions into a tradable probability signal—something traditional models struggle to achieve.

2. How Is Probability Pricing Interpreted?

In prediction markets, the price of an outcome often directly represents the market’s implied probability. For example:

• A price of 0.65 suggests the market believes there’s about a 65% chance of the event occurring
• Price changes reflect dynamic shifts in consensus

For researchers and traders, this “real-time probability curve” is more valuable than single-point forecasts.

III. Macro Finance and Asset Events: ETFs, Interest Rates, and Policy Expectations

As the line between crypto markets and traditional finance blurs, prediction markets are increasingly used to price macro financial events.

1. Typical Prediction Targets

• Whether an ETF will be approved
• Whether interest rates will change within a specific time window
• Whether regulatory policies will be introduced or delayed

These events don’t directly generate cash flow but can profoundly affect asset prices. Prediction markets offer an independent price discovery mechanism for these “leading variables.”

2. Prediction Markets vs. News Trading

Compared to short-term trading based on news, prediction markets tend to focus on:

• Proactive positioning
• Long-term holding
• Probability-based rather than directional bets

This makes prediction markets useful as event hedging tools—not just instruments for speculation.

IV. Crypto-Native Events: Mainnet Launches, Airdrops, and Protocol Decisions

In the Web3 world, prediction markets are even more adaptable.

1. Predictability of Protocol-Level Events

Crypto protocols operate with highly transparent development cycles, such as:

• Will the mainnet launch on schedule?
• Will upgrades pass governance votes?
• Will tokens be issued by a certain date?

These events are naturally suited to be structured as prediction markets.

2. Prediction Markets as “Sentiment & Expectation Dashboards”

On-chain prediction markets often reflect genuine expectations earlier than social media. Price movements can reveal:

• Market doubts about project progress
• Turning points in community confidence
• Early positioning by information leaders

V. On-Chain Behavior Prediction: Moving from “Events” to “Behavioral Patterns”

The next evolution for prediction markets is expanding from single events to forecasting behavior patterns.

1. The Rise of Behavioral Prediction Markets

Typical questions include:

• Will a specific address perform a certain action within a given timeframe?
• Will a protocol’s TVL surpass a particular threshold?
• Will one chain’s trading volume exceed another’s?

These predictions aren’t about binary outcomes but about whether behavioral trends will materialize.

2. Integrating On-Chain Data

When prediction markets are combined with on-chain analytics tools, they can enable:

• Data-driven market judgments
• Pricing expressions of behavioral expectations
• Early warnings for abnormal activity

Such applications are gaining attention from research institutions and professional traders.

VI. Prediction Markets as Research and Risk Management Tools

Prediction markets are becoming not only trading instruments but also foundational research infrastructure.

1. Value for Researchers

• Rapid hypothesis testing
• Observing divergence and consensus
• Capturing “minority but correct” signals

2. Value for Institutions and Protocols

• Assessing the community’s true stance on proposals
• Early detection of risk events
• Expressing opinions through market signals rather than votes

To some extent, prediction markets are supplementing—or even replacing—traditional governance voting.

VII. Application Boundaries and Real-World Constraints

Despite rapid expansion in use cases, prediction markets still face practical limitations:

• Legal and regulatory uncertainty
• High cost of defining events
• Insufficient liquidity for long-tail events

As a result, prediction markets are best suited for high-attention, high-information-density events rather than unlimited expansion.