Elections, policy decisions, economic releases, and other public events create expectations long before the final outcome is known.
FinFeedAPI Prediction Markets API provides access to market listings and metadata, latest and historical trades and quotes, OHLCV candles, current order-book snapshots, historical order-book updates where supported, and historical market records through REST, JSON-RPC, and MCP. Forecasting teams can use this data to study how market prices and market-derived expectation signals change as events develop.
A forecast is rarely static.
New polling, economic data, policy announcements, debates, court decisions, campaign developments, or other public information can change expectations before an event resolves.
The difficult part is building a consistent history of those changing expectations across prediction markets.
Polls, research notes, and economic forecasts may be published on different schedules.
Different platforms use different identifiers, market structures, outcomes, and data formats.
A current price means more when you can see how that market traded previously.
Resolution rules, wording, liquidity, available outcomes, and venue mechanics can differ.
Researchers still need to investigate trades, quotes, liquidity, timing, contract design, and external information around the move.
Imagine a political or economic contract is currently trading at a particular price.
The useful forecasting questions go further:
Prediction-market prices provide market-based observations, not certainty.
FinFeedAPI provides structured market records across supported prediction-market venues. Researchers can work with standardized fields such as market identifiers, titles, descriptions, outcomes, prices, status, exchange identifiers, and outcome types rather than building a separate integration for each venue.
Historical OHLCV data provides time-series views of market prices across available periods. This makes it possible to study trends, reversals, and historical repricing around political or economic events.
FinFeedAPI normalizes prediction-market data from supported platforms through one API layer.
Forecasting teams can build cross-venue research workflows without maintaining completely separate integrations for every supported platform.
Comparable-looking markets still need to be checked for differences in wording, outcomes, resolution criteria, liquidity, and market structure.
Current order-book snapshots provide bids and asks where supported. Researchers can use this information to inspect current spread, available depth, and liquidity conditions rather than interpreting the latest market price in isolation.
Activity resources provide latest, recent, and historical trade and quote data where supported. This gives researchers additional market context around price movements without implying anything about individual participants or their motivations.
Follow supported election-related contracts across time and use OHLCV data to study how market prices changed before resolution.
Researchers can compare these movements with selected public events without treating market prices as guaranteed predictions.
Track supported contracts related to future policy outcomes and identify periods when market prices materially repriced. The research workflow can then investigate what external information was available around those periods.
Use supported markets related to economic events or outcomes as another signal alongside conventional macroeconomic indicators and forecasts.
Prediction-market observations can complement rather than replace other forecasting inputs.
Identify comparable markets across supported platforms and compare their prices or historical trajectories.
Before combining them, verify contract wording, resolution criteria, outcome structure, liquidity, and market status.
Use historical OHLCV to identify significant price moves or changes in direction. Historical trades and quotes, where supported, can then provide additional context around those periods.
Use structured latest and historical data to build internal dashboards showing selected prediction markets, price history, trades and quotes, current depth where supported, and market status.
Because FinFeedAPI does not provide Prediction Markets WebSocket streaming, current-data dashboards should use an appropriate polling workflow.
| Prediction Markets Capability | Forecasting Application | Example |
|---|---|---|
| Market Listings & Metadata | Market discovery | Identify supported contracts related to an election, policy decision, or economic event |
| Latest Market Data | Current expectation signal | Retrieve the latest market price or price-based implied expectation where applicable |
| Historical OHLCV | Price-history analysis | Study how market prices evolved across available periods |
| Trades & Quotes | Market-movement context | Examine latest, recent, or historical activity where supported |
| Current Order Book | Liquidity context | Inspect bids, asks, spread, and available depth where supported |
| Historical Order-Book Updates | Historical liquidity research | Study changes in order-book conditions where supported |
| Historical Market Records | Event research | Retrieve historical market metadata and context for supported markets |
| REST / JSON-RPC / MCP | Forecasting applications | Connect supported prediction-market data to research, models, dashboards, and AI workflows |
Prediction-market prices should be treated as market-derived signals. FinFeedAPI does not determine whether a market price is an accurate forecast or how much weight it should receive relative to another forecasting source.
| Forecasting Workflow | Before | After With Prediction Markets API |
|---|---|---|
| Market discovery | Researchers browse prediction platforms separately | Supported markets can be discovered through a normalized API layer |
| Price history | Historical market movements are difficult to collect consistently | OHLCV provides structured historical price series |
| Venue comparison | Each platform requires separate integration and parsing | Supported venues can be accessed through a common interface |
| Current market context | Latest price may be viewed without liquidity information | Current order-book snapshots add bids, asks, spread, and depth where supported |
| Activity analysis | Price movements may be studied without trade and quote context | Latest, recent, and historical trades and quotes add context where supported |
| Contract research | Market identifiers and metadata differ by platform | Normalized fields simplify downstream research workflows |
| Forecasting models | Prediction-market data requires custom collection and normalization | Structured data can feed forecasting and analytical pipelines |
| Current monitoring | Teams may expect unsupported streaming access | Current resources can be polled through supported interfaces at an appropriate cadence |
REST supports workflows around market discovery, individual market retrieval, historical market records, OHLCV, trades and quotes, current order books, and other supported prediction-market resources.
This works well for research scripts, forecasting pipelines, dashboards, and scheduled monitoring.
FinFeedAPI also provides read-only JSON-RPC access to supported Prediction Markets resources.
This can fit applications that prefer RPC-style integration for data retrieval.
MCP gives compatible AI applications structured access to supported Prediction Markets tools.
This can support market discovery and data retrieval while forecast interpretation remains part of the user's own methodology.
Prediction Markets API does not provide WebSocket streaming.
Applications that need refreshed current market information can poll supported current endpoints at a cadence appropriate to their use case and data requirements.
A forecasting workflow can follow a clear sequence:
Use structured market discovery to find relevant contracts, historical OHLCV to study how prices changed, trades and quotes to investigate market activity, and current order-book snapshots to examine liquidity where supported.
FinFeedAPI Prediction Markets API gives forecasting teams a normalized data layer for researching political and economic expectations across supported prediction-market venues without maintaining separate integrations for each platform.
