Mapping CIKs, Entity Names and Tickers (last update October 2025)

Identification Misalignment

The goal of this project is to provide a unified, programmatic mapping between CIKs, tickers and entity names via API, enabling fast and bulk reconciliation of EDGAR filings with market data, covering every registered company, fund, subsidiaries, trusts, funds and other entity that ever filed with the SEC.

Data providers like Bloomberg identify entities through name, ticker, and ISIN, whereas the SEC's EDGAR system relies primarily on name and its unique 10-digit CIK identifier (with occasional tickers, but no ISIN, CUSIP, LEI, etc.).
This misalignment complicates reconciliation between Bloomberg/other data sources and EDGAR.

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Data Sources: SEC Files

Several SEC sources provide entities mapping information, including bulk data files recompiled nightly and made available via the SEC EDGAR API (kindly note that the following description is referred to the data as of August 2025, as an example):

1. companyfacts.zip: 18,826 entities. Each record is a JSON file keyed by CIK (e.g., CIK0002053927.json) and includes CIK and name.
2. submissions.zip: 927,405 entities. Each JSON file includes CIK, name, and ticker. Tickers are populated for 6,813 entities.

Moreover an additional file used is: 3) company_tickers_exchange.json: 7,847 entities, including CIK, name, and ticker.

Coverage and consistency:

• All 18,826 entities in companyfacts.zip are present in submissions.zip, but only 41% of entities names match exactly due to naming variations.
• All 7,847 entities in company_tickers_exchange.json are present in submissions.zip, with 87% exact name matches.

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Additional Relevant Source: EDGAR Full-Index

The EDGAR full-index archives SEC/EDGAR filings:

• Provides comprehensive historical coverage dating back to 1993.
• Each entry is identified by name and CIK, allowing consistent linkage to other datasets.

In the cik-lookup-data.txt file:

• Each line reports the name and the CIK.

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Integration Approach

To reconcile inconsistencies, two JSON dictionary were created using CIK as the key and ticker as the key:

• result_cik_keyed.json.gz
• result_ticker_keyed.json.gz

In the JSON files:

• Each record integrates entities names, tickers and CIKs from all three sources when available.
• Ensures the most complete representation of each entity and facilitates cross-referencing between Bloomberg/data providers and SEC/EDGAR.

Example entry for CIK 0000794685 in "result_cik_keyed":

"0000794685": {
  "primary_ticker": "GAB",
  "secondary_securities": ["GAB-PG", "GAB-PH", "GAB-PK"],
  "denomination": ["GABELLI EQUITY TRUST INC"]
}

Example entry for ticker GAB in "result_ticker_keyed":

"GAB": {
  "secondary_securities": ["GAB-PG", "GAB-PH", "GAB-PK"],
  "denomination": ["GABELLI EQUITY TRUST INC"],
  "CIK": "0000794685",
}

EDGAR CIK-Ticker API

I built an API allowing data retrieval and using an input either the CIK or the ticker.

Base URL: https://edgar-cik-api.onrender.com

Endpoints:

1. Lookup by CIK
Retrieve entity information using the SEC CIK.
GET /cik/{cik}

Example in Python:

import requests

url = "https://edgar-cik-api.onrender.com/cik/0000320193"
response = requests.get(url)
data = response.json()
print(data)

{
  "primary_ticker": "AAPL",
  "secondary_securities": ["AAPL-PG", "AAPL-PH"],
  "denomination": ["APPLE INC"]
}

2. Lookup by ticker
Retrieve entity information using the ticker.
GET /ticker/{ticker}

Example in Python:

import requests

url = "https://edgar-cik-api.onrender.com/ticker/gab"
response = requests.get(url)
data = response.json()
print(data)

{
  "secondary_securities": ["AAPL-PG", "AAPL-PH"],
  "denomination": ["GABELLI EQUITY TRUST INC"],
  "CIK": "0000320193",
}

Note: As the API is hosted on a free Render plan, cold starts may take a few seconds.