Prediction markets are getting more serious.
For years, most of the attention went to elections, sports, crypto, and headline-driven events. ForecastEx takes a different direction.
Interest rates. Inflation. GDP. Employment. Climate. Economic policy.
These are events that already move bonds, currencies, equities, and derivatives.
Now they can also be expressed as probabilities.
And ForecastEx prediction market data is now available through the FinFeedAPI Prediction Markets API.
That means researchers, developers, quants, and AI teams can analyze ForecastEx alongside other prediction market venues through one standardized data layer.
What Is ForecastEx?
ForecastEx is a prediction market operated within Interactive Brokers Group.
More importantly, it is a CFTC-registered Designated Contract Market (DCM) and Derivatives Clearing Organization (DCO).
That makes its focus a little different from many prediction platforms.
Think less:
“Who will win this game?”
And more:
“Will the Federal Reserve cut rates?”
“Will inflation exceed this level?”
“Where will unemployment be?”
“Will a specific climate benchmark be reached?”
ForecastEx turns questions like these into tradable contracts.
And every trade leaves behind something useful:
a market price for what participants believe will happen next.
How ForecastEx Contracts Work
The idea is simple.
A Forecast Contract represents a specific future outcome.
You take a Yes or No position depending on what you expect to happen.
Prices move between $0.01 and $0.99.
So if a Yes contract trades at $0.72, the market is effectively pricing the outcome at roughly a 72% probability.
As expectations change, the price changes.
New inflation number?
The market reacts.
Unexpected Fed comment?
It reacts again.
Employment data surprises?
Another adjustment.
Instead of seeing only the final forecast, you can follow how expectations evolved before the event happened.
That history is where the data becomes especially interesting.
ForecastEx also pays interest on cash balances associated with positions, which can make longer-term contracts more practical to hold.
And because contracts can cover different horizons, researchers can observe how expectations differ across weeks, months, quarters, or even longer periods.
From Economic Data to Market Probability
ForecastEx contracts can be tied to some of the most closely watched economic and climate indicators in the world.
Resolution can depend on official sources such as:
- U.S. Bureau of Labor Statistics (BLS) for CPI, employment, and unemployment data
- Bureau of Economic Analysis (BEA) and U.S. Census Bureau for economic indicators
- National Oceanic and Atmospheric Administration (NOAA) for climate and temperature data
- University of Michigan for consumer sentiment indicators
But ForecastEx adds another layer to those datasets.
An official CPI release tells you what inflation was.
A prediction market can tell you what participants expected it to be before the number arrived.
And, even more importantly, how that expectation changed over time.
That gives researchers a historical record of market belief.
Why ForecastEx Data Is Interesting for Quants
Traditional market data answers one question extremely well:
What happened to the price?
Prediction market data answers another:
What did the market think was going to happen?
Put the two together and you can start asking much better questions.
Suppose ForecastEx probabilities of a Fed rate cut jump from 35% to 60%.
What happens to Treasury yields at the same time?
What happens to SOFR futures?
The dollar?
Bank stocks?
Equity volatility?
Instead of studying an asset move in isolation, researchers can compare it with a direct market-based probability of the underlying event.
That opens the door to several interesting applications.
Cross-Market Signals
Compare ForecastEx probabilities with traditional financial instruments.
A change in the probability of a rate decision, inflation outcome, or economic release may appear before or move differently from the corresponding reaction in bonds, currencies, equities, or derivatives.
Those differences can become signals themselves.
Better Macro Research
Economists already compare forecasts with actual releases.
Prediction markets add another dataset to that process.
You can compare:
economist consensus vs. prediction market probability vs. actual outcome.
Over hundreds of events, you can start measuring which signals were useful, when they became useful, and how quickly they incorporated new information.
AI and Machine Learning
This is where prediction market data gets especially interesting.
AI systems are very good at consuming text.
News. Filings. Transcripts. Social media. Research.
But text still needs to be interpreted.
Prediction markets give models something different:
a continuously changing numerical representation of expectations.
Instead of asking an AI system to infer whether the market expects a rate cut from thousands of articles, you can give it a probability series directly.
That probability can become another feature in a model.
Combine it with:
- stock OHLCV
- interest rates
- FX data
- economic releases
- SEC filings
- news or sentiment signals
And the model gets both sides of the story:
what markets are doing and what participants expect to happen next.
ForecastEx Data Through FinFeedAPI
The difficult part of working with multiple prediction markets is rarely understanding the contracts.
It is the infrastructure.
Every venue has its own identifiers, schemas, market structures, and access methods.
That becomes painful when you want to compare several venues at once.
FinFeedAPI standardizes that data.
With the addition of ForecastEx, developers can work with ForecastEx alongside prediction market sources including:
Polymarket, Kalshi, Myriad, Manifold, Hyperliquid Outcome Markets, Gemini Prediction Markets, Pascal, and Crypto.com Prediction Markets.
Through the Prediction Markets API, developers can access standardized market metadata and historical market data using interfaces including REST, JSON-RPC, and MCP.
The result is much simpler.
Instead of building a separate research pipeline around every prediction venue, you can work with multiple markets through one consistent data model.
The Bigger Opportunity Is Comparing Markets
ForecastEx is useful on its own.
But the more interesting opportunity appears when you stop looking at prediction markets individually.
Imagine two venues pricing the same macro event differently.
One market says 58%.
Another says 71%.
Now you have a new question:
Why?
Maybe the participants are different.
Maybe liquidity is different.
Maybe one market reacted faster.
Maybe one group has information the other has not incorporated yet.
Those differences are data too.
As prediction markets expand, researchers won't just analyze whether a probability went up or down.
They'll analyze who moved first, which market was more accurate, and where expectations diverged before important events.
ForecastEx adds another important piece to that picture.
And its data is now available through FinFeedAPI Prediction Markets API.
Explore ForecastEx Data
Explore ForecastEx markets, historical data, and prediction market endpoints in the FinFeedAPI Prediction Markets API documentation.
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