Databento releases corporate actions dataset and reference data API

We're excited to announce the release of our corporate actions data, the first of several datasets that will be available through our new reference data API. Corporate actions provide historical and upcoming company events that affect security prices and listing statuses.

This dataset offers global coverage from 215 exchanges worldwide, including over 310,000 listed and delisted stocks, ETPs, DRs, bonds, and other types of securities from more than 85,000 issuers and companies. Each message captures a corporate action event for a specific listing with continuous records. This means that even if a security is delisted and later relisted, it's continuously tracked to prevent gaps in the time series.

Over 60 different types of corporate events are included in this dataset, such as dividends, splits, mergers and acquisitions, new listings, and more. For each event type, a message generally consists of the following:

• Point-in-time record timestamp.
• Event ID, event type, and any applicable subtypes or related events.
• Date fields for the event date, effective date, when the event was created, listing date, and delisting date (where applicable).
• Identifiers for the listing and its status; the security and its type, description, and par value; its issuer, and the exchange(s) on which it's listed.
• Country and currency-related information, as well as the ISIN, US, and local codes.

You can find a complete list of event types and fields in our documentation.

Corporate actions data is available over our HTTP reference data API and official Python client library. The reference API is based on the same conventions and timestamp formats as our historical and live APIs.

To access this dataset, contact our sales team using the form on our corporate actions page. Pricing starts at $299 per month.

This example shows how to request dividend dates using Python.

import databento as db

client = db.Reference("YOUR_API_KEY")

df = client.corporate_actions.get_range(
    symbols=["NVDA"],
    start="2018-05-01",
    end="2024-05-01",
    index="ex_date",
    events=["DIV"],
    countries=["US"],
)

# Ex-dividend, payment date, payment type, and amount
print(df[["payment_date", "payment_type", "gross_dividend"]])

More in-depth tutorials for dividends, new listings, mergers and demergers, and splits and reverse splits can be found in our docs.

The data is updated four times daily and is delivered directly from Databento’s API servers.

We'll expand Databento's reference data catalog in Q4 of 2024 with the addition of the adjustment factors and security master datasets.

Adjustment factors are used to ensure that historical data remains consistent across different time periods when the security undergoes significant capital changes.

Our adjustment factors dataset provides a simpler way to apply adjustments as compared to the raw corporate actions dataset. It consolidates all types of events—not only forward and reverse splits, but also more complex events like dividends, redemptions, buybacks, and new issues—into a single adjustment ratio on any given day.

Companies often change their corporate names or securities' ticker symbols, which can create confusion when joining historical data with real-time data. The security master dataset will provide a comprehensive range of external symbology mappings since 2005, including Bloomberg FIGI, ISINs, CFIs, FISNs, and CIKs, to enable the tracking of securities across different identifiers and naming conventions.