Trading Co-Pilot: News Intelligence
NEVER MISS MARKET MOVING NEWS AGAIN
Permutable’s News Intelligence platform turns global news chaos into structured, actionable insights – complete with quantified impact scores across major asset classes.
Our institutional-grade system processes thousands of sources hourly, detecting geopolitical risks, economic releases, and market trends with millisecond latency.
Gain access to 10+ years of historical data for robust backtesting and receive real-time alerts via enterprise API. While others manually interpret headlines, you’ll act on opportunities faster with AI-driven, systematic intelligence.
Technical Overview
Permutable's structured news intelligence platform delivers institutional-grade market analysis for quantitative workflows. Our solution is designed for asset managers, hedge funds, and financial institutions seeking to integrate real-time news and event data into their trading and risk management systems. With a focus on transparency and actionable insights, the platform enables users to identify market-moving events, track sentiment, and monitor macroeconomic and geopolitical developments across global markets.
Implementation Use Cases
Full Coverage
Access broad and deep coverage across all major asset classes and geographies. Our platform captures:
Real-Time
Stay ahead with live hourly updates from our API, designed for systematic and quantitative workflows:
10 Year History
Unlock a decade of structured news intelligence for robust backtesting and research:
Permutable Co-Pilot API enables programmatic access to structured news data with millisecond latency and enterprise-grade reliability. Full documentation is available at https://copilot-api.permutable.ai/redoc, including Python, R, and Java client libraries with webhook support.
API Reference
Retrieve a paginated list of financial asset events for a given ticker, ordered by date in descending order by default. Supports date range filtering.
GET
/v1/events/financial/{ticker}/{ticker}
Parameters
Name | Description |
---|---|
ticker
required
string
|
Ticker of the entity to fetch events for |
start_date
string (date)
|
Earliest date of the events to fetch (max 3 months before current date) |
end_date
string (date)
|
Latest date of the events to fetch |
limit
integer
Range: 1-100
|
Number of events per page |
offset
integer
Minimum: 0
|
Starting position of the current page |
Request Sample (Python)
import requests
# Replace with your actual credentials
API_KEY = "your-api-key"
# Headers
headers = {
"x-api-key": API_KEY,
}
# Query parameters
params = {'start_date': '2024-11-25', 'end_date': '2024-11-25', 'limit': 10, 'offset': 0}
# Make the request
response = requests.get(
"https://copilot-api.permutable.ai/1/events/fundamental/ticker/BZ_COM",
headers=headers,
params=params
)
# Check for errors
response.raise_for_status()
# Get the response data
data = response.json()
print(data)
Responses
Code | Description | Links |
---|---|---|
200 | Successful response | No links |
Response Type
application/json
Sample Response
{ "events": [ {"asset": "Brent Crude Oil", "direction": "bullish", "event_date": "2025-05-17T08:43:59.837", "headline": "Ukraine-Russia conflict continues to escalate...", "description": "The escalation of the Ukraine-Russia conflict primarily affects geopolitical stability and may impact global grain markets, but it does not have a direct impact on Brent crude oil prices. Our regional analysts emphasize that the oil market is more affected by OPEC+ production decisions and global demand patterns.", "event_type": "geopolitical conflict", "source_count": 3, "sources": ["Reuters", "Bloomberg", "BBC"], "impact": 0.65 }, {"asset": "Gold", "direction": "bearish", "event_date": "2025-05-16T14:30:00.000", "headline": "Gold prices continue to rise amid global economic uncertainty...", "description": "Gold prices continue to rise amid global economic uncertainty and geopolitical tensions.", "event_type": "market trends", "source_count": 3, "sources": ["Reuters", "CNBC", "Bloomberg"], "impact": 0.42 } ], "total": 26, "page": 1, "pages": 3 }
Sample Data
Asset | Event Name | Date | Sentiment | Topic | Summary | Source |
---|
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