Is there a way by which I can get a list of CIK of all registered stocks at the SEC?
14 Answers
The EDGAR FTP should have all of the information you need. Here is the list from that page in text format. Keep in mind a given CIK can be associated with multiple names through time.
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4
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1$\begingroup$ There isn't one I'm aware of. Mappings require legwork and most who have built one aren't always readily willing to share it, especially for a universe this large. $\endgroup$– jeff mMay 31, 2013 at 20:23
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1$\begingroup$ @Jean CIK-Ticker mapping by RandAndFiled: rankandfiled.com/#/data/tickers $\endgroup$ Sep 29, 2016 at 18:28
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$\begingroup$ @AntonTarasenko do you know the source of this info? Is it static? How do they compile this? $\endgroup$– eggie5Jun 14, 2017 at 21:14
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$\begingroup$ @eggie5 I don't know. I made my own ticker-CIK dataset after all. Based on the up-to-date SEC ticker data. $\endgroup$ Jun 15, 2017 at 6:37
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2$\begingroup$ This mapping is no longer maintained as of 7/1/21 according to sec.gov/os/accessing-edgar-data $\endgroup$ Dec 18, 2021 at 0:18
This website has what you're looking for in downloadable csv/Excel format:
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2$\begingroup$ While useful, this seems to be a subset of the CIK's listed in this answer. $\endgroup$– Bob Jansen ♦May 28, 2017 at 9:03
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$\begingroup$ Rank and filed seems to no longer be active. The site gives a 502. $\endgroup$ Dec 18, 2021 at 0:18
As of now, I know of no good method.
The tedious part about all of this is that there is no company name standard apparent to me, as CIK company name, exchange company name, and legal company name can all be different. I have to get my hands dirty with the method I use.
I only trade options, so I download the CBOE's master list in csv and input into my database. I think the stock exchanges post something similar.
This is the tedious part: you can use the established company name to ticker search which is difficult to parse or this other search that gives everything on a given result. I use the second search.
For this, I made a simple php script that iterates through each ticker I receive from the CBOE, searching first the entire company name then each word individually, both except for words like "the", "company", "corporation", "inc", etc and dump the results into a database.
You'll see that with the "other search" there are two results: a company page if there's only result or a company list if there're multiple. Both are easy to parse.
When there's 1 result for the search with the "sanitized" entire company name, I just went with that initially and started on the ones with multiples (rare with full name search) or no results (sometimes with full name search). Over time, I have confirmed all manually.
The manual inspection never ends. Companies change names and tickers.
I will now parse with jeff m's link.
Yahoo Finance has a mapping of tickers to CIKs, which is visible on their SEC Filings pages, e.g. http://finance.yahoo.com/q/sec?s=KO+SEC+Filings
This page links to documents on EDGAR, and at the bottom of the page there is a link, "View All Filings on EDGAR Online", which contains the cik as a URL parameter:
<a href="http://www.edgar-online.com/brand/yahoo/search/?cik=21344" data-rapid_p="39">
<strong>View All Filings on EDGAR Online</strong>
</a>
And indeed, Coca-Cola's CIK is 21344.
Incorporating pabtorre's code for easier reading:
import re
import urllib2
def get_cik(ticker):
''' this function uses yahoo to translate a ticker into a CIK '''
url = "http://finance.yahoo.com/q/sec?s=%s+SEC+Filings" % (ticker)
return int(re.findall('=[0-9]*',
str(re.findall('cik=[0-9]*',
urllib2.urlopen(url).read())[0]))[0][1:])
This can probably be tidied up a bit but I gave it a try and it worked.
Cerin's comment referenced a discussion thread that lead me to discover in fact you can query EDGAR directly with ticker names. it's not clear to me why this wasn't apparent before, perhaps it's a new feature. If you go to EDGAR's Company Search page you can type in a ticker and get the associated CIK and companies filings; here's the result page for KO again - even better, the data is served up as XML, making it very easy to parse.
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$\begingroup$ this can be done in python with a few lines of code.
import re import urllib2 def get_cik(ticker): ''' this function uses yahoo to translate a ticker into a CIK ''' url = "http://finance.yahoo.com/q/sec?s=%s+SEC+Filings"%(ticker) return int(re.findall('=[0-9]*', str(re.findall('cik=[0-9]*', urllib2.urlopen(url).read())[0]))[0][1:])
$\endgroup$– PabTorreJan 9, 2014 at 19:18 -
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$\begingroup$ This doesn't work for a lot of tickers. Try LEXG, JAMN for example... $\endgroup$– eggie5Sep 13, 2016 at 22:14
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$\begingroup$ @egg Yep. It's an additional fetch if it can't find the text cik. Just parse for the link to edgar and follow it, then scrape that page for the cik. Narrow test case was LEXG. $\endgroup$ Mar 25, 2017 at 12:50
My hard-fought results (14,452 CIKs and their tickers):
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$\begingroup$ Interesting, thanks for doing this and sharing! Can you describe your methodology? How can someone else replicate or verify your work? $\endgroup$– dimo414Sep 14, 2016 at 1:39
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1$\begingroup$ I've taken the liberty to parse your list and produce a pipe delimited file, here's the gist gist.github.com/x011/b6d22c462a2e4ab8d6c1f1eab42a0a83, tks! $\endgroup$ Mar 13, 2017 at 2:07
You can get this directly from the SEC.
In text format: https://www.sec.gov/include/ticker.txt
Sample:
a 1090872 aa 1675149 aaap 1611787 aacg 1420529 aach 1606180 aacqu 1802457 aagh 1098009 ...
In JSON format: https://www.sec.gov/files/company_tickers.json (For mutual funds and ETFs https://www.sec.gov/files/company_tickers_mf.json)
Sample:
{ "0":{"cik_str":1750,"ticker":"AIR","title":"AAR CORP"}, "1":{"cik_str":1800,"ticker":"ABT","title":"ABBOTT LABORATORIES"}, "2":{"cik_str":1961,"ticker":"WDDD","title":"WORLDS INC"}, "3":{"cik_str":2034,"ticker":"ACET","title":"ACETO CORP"}, ... }
More information about getting EDGAR data: https://www.sec.gov/edgar/searchedgar/accessing-edgar-data.htm
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$\begingroup$ Your first answer was already listed by nightcrawler500. $\endgroup$ Jul 2, 2020 at 17:16
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$\begingroup$ The JSON is great. Somehow orcl 1341439 has a duplicate entry. $\endgroup$ Sep 7, 2020 at 1:40
As noted on the SEC EDGAR data access website, the tickers.txt
file has been phased out and is no longer updated as of 7/1/21.
As of 2021 onwards, the SEC provides the following methods for obtaining CIK, ticker, and exchanges:
- Ticker, CIK, EDGAR conformed company name associations: https://www.sec.gov/files/company_tickers.json
- EDGAR conformed company name, CIK, ticker, exchange associations: https://www.sec.gov/files/company_tickers_exchange.json
- Mutual fund CIK, series ID, class ID, ticker: https://www.sec.gov/files/company_tickers_mf.json
In order to ease the CIK mapping experience, I recently developed a Python package called sec-cik-mapper
that provides a programmatic interface for obtaining these CIK mappings (install with pip install -U sec-cik-mapper
). You can use it as follows once installed:
Stocks
>>> from sec_cik_mapper import StockMapper
>>> from pathlib import Path
# Initialize a stock mapper instance
>>> mapper = StockMapper()
# Get mapping from CIK to tickers
>>> mapper.cik_to_tickers
{'0000320193': {'AAPL'}, '0000789019': {'MSFT'}, '0001652044': {'GOOG', 'GOOGL'}, ...}
# Get mapping from ticker to CIK
>>> mapper.ticker_to_cik
{'AAPL': '0000320193', 'MSFT': '0000789019', 'GOOG': '0001652044', ...}
# Get mapping from CIK to company name
>>> mapper.cik_to_company_name
{'0000320193': 'Apple Inc.', '0000789019': 'Microsoft Corp', '0001652044': 'Alphabet Inc.', ...}
# Get mapping from ticker to company name
>>> mapper.ticker_to_company_name
{'AAPL': 'Apple Inc.', 'MSFT': 'Microsoft Corp', 'GOOG': 'Alphabet Inc.', ...}
# Get mapping from ticker to exchange
>>> mapper.ticker_to_exchange
{'AAPL': 'Nasdaq', 'MSFT': 'Nasdaq', 'GOOG': 'Nasdaq', ...}
# Get mapping from exchange to tickers
>>> mapper.exchange_to_tickers
{'Nasdaq': {'CYRN', 'OHPAW', 'SANW', ...}, 'NYSE': {'PLAG', 'TDW-WTB', 'RS', ...}, 'OTC': {'ZICX', 'LTGJ', 'AVNI', ...}, ...}
# Get mapping from CIK to exchange
>>> mapper.cik_to_exchange
{'0000320193': 'Nasdaq', '0000789019': 'Nasdaq', '0001652044': 'Nasdaq', ...}
# Get mapping from exchange to CIKs
>>> mapper.exchange_to_ciks
{'Nasdaq': {'0000779544', '0001508171', '0001060955', ...}, 'NYSE': {'0000764478', '0000008818', '0001725057', ...}, 'OTC': {'0001044676', '0001592411', '0001284452', ...}, ...}
# Save CIK, ticker, exchange, and company name mappings to a CSV file
>>> csv_path = Path("example_mappings.csv")
>>> mapper.save_metadata_to_csv(csv_path)
# Get raw pandas dataframe
>>> mapper.raw_dataframe
CIK Ticker Name Exchange
0 0000320193 AAPL Apple Inc. Nasdaq
1 0000789019 MSFT Microsoft Corp Nasdaq
2 0001652044 GOOG Alphabet Inc. Nasdaq
3 0001018724 AMZN Amazon Com Inc Nasdaq
4 0001318605 TSLA Tesla, Inc. Nasdaq
... ... ... ... ...
13184 0001866816 OLITU Omnilit Acquisition Corp. Nasdaq
13185 0001870778 OHAAU Opy Acquisition Corp. I Nasdaq
13186 0001873324 PEPLW Pepperlime Health Acquisition Corp Nasdaq
13187 0001877557 WEL-UN Integrated Wellness Acquisition Corp NYSE
13188 0001877787 ZGN-WT Ermenegildo Zegna Holditalia S.P.A. NYSE
[13189 rows x 4 columns]
Mutual Funds
>>> from sec_cik_mapper import MutualFundMapper
>>> from pathlib import Path
# Initialize a mutual fund mapper instance
>>> mapper = MutualFundMapper()
# Get mapping from CIK to tickers
>>> mapper.cik_to_tickers
{'0000002110': {'CRBYX', 'CEFZX', 'CSSRX', ...}, '0000002646': {'IIBPX', 'IPISX', 'IIBTX', ...}, '0000002663': {'IMSXX', 'VMTXX', 'IVMXX', ...}, ...}
# Get mapping from ticker to CIK
>>> mapper.ticker_to_cik
{'LACAX': '0000002110', 'LIACX': '0000002110', 'ACRNX': '0000002110', ...}
# Get mapping from CIK to series ID
>>> mapper.cik_to_series_ids
{'0000002110': {'S000009184', 'S000033622', 'S000009185', ...}, '0000002646': {'S000008760'}, '0000002663': {'S000008702'}, ...}
# Get mapping from ticker to series ID
>>> mapper.ticker_to_series_id
{'LACAX': 'S000009184', 'LIACX': 'S000009184', 'ACRNX': 'S000009184', ...}
# Get mapping from series ID to CIK
>>> mapper.series_id_to_cik
{'S000009184': '0000002110', 'S000009185': '0000002110', 'S000009186': '0000002110', ...}
# Get mapping from series ID to tickers
>>> mapper.series_id_to_tickers
{'S000009184': {'CEARX', 'CRBYX', 'ACRNX', ...}, 'S000009185': {'ACINX', 'CACRX', 'CAIRX', ...}, 'S000009186': {'LAUCX', 'LAUAX', 'CUSAX', ...}, ...}
# Get mapping from series ID to class IDs
>>> mapper.series_id_to_class_ids
{'S000009184': {'C000024956', 'C000122737', 'C000024957', ...}, 'S000009185': {'C000024958', 'C000122739', 'C000097733', ...}, 'S000009186': {'C000024962', 'C000024964', 'C000122740', ...}, ...}
# Get mapping from ticker to class ID
>>> mapper.ticker_to_class_id
{'LACAX': 'C000024954', 'LIACX': 'C000024956', 'ACRNX': 'C000024957', ...}
# Get mapping from CIK to class IDs
>>> mapper.cik_to_class_ids
{'0000002110': {'C000024958', 'C000024969', 'C000024957', ...}, '0000002646': {'C000023849', 'C000074893', 'C000028785', ...}, '0000002663': {'C000023718', 'C000028786', 'C000076529', ...}, ...}
# Get mapping from class ID to CIK
>>> mapper.class_id_to_cik
{'C000024954': '0000002110', 'C000024956': '0000002110', 'C000024957': '0000002110', ...}
# Get mapping from class ID to ticker
>>> mapper.class_id_to_ticker
{'C000024954': 'LACAX', 'C000024956': 'LIACX', 'C000024957': 'ACRNX', ...}
# Save CIK, ticker, series ID, and class ID mappings to a CSV file
>>> csv_path = Path("mutual_fund_mappings.csv")
>>> mapper.save_metadata_to_csv(csv_path)
# Get raw pandas dataframe
>>> mapper.raw_dataframe
CIK Ticker Series ID Class ID
0 0000002110 LACAX S000009184 C000024954
1 0000002110 LIACX S000009184 C000024956
2 0000002110 ACRNX S000009184 C000024957
3 0000002110 CEARX S000009184 C000122735
4 0000002110 CRBRX S000009184 C000122736
... ... ... ... ...
29237 0001860434 SIHY S000072555 C000228888
29238 0001860434 SIFI S000072556 C000228889
29239 0001860434 INNO S000073580 C000230585
29240 0001877493 BTF S000074058 C000231452
29241 0001877493 VBB S000075054 C000233857
[29242 rows x 4 columns]
```
Edit: this no longer works.
The following is a list of every CIK at the SEC:
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$\begingroup$ do you know where the documentation for this page/resource is? $\endgroup$– eggie5Jun 14, 2017 at 21:19
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1$\begingroup$ This no longer works as of about 3 months ago $\endgroup$ Nov 7, 2017 at 21:55
I developed a RESTful JSON API (https://mapping-api.herokuapp.com/).
You can send any CIK, company ticker, or company name, and the API returns a JSON response (see examples below) containing the mapping. Retrieving all companies listed on a specific exchange also works.
Examples
Resolve by CIK
Request: GET https://mapping-api.herokuapp.com/cik/:cik
Replace :cik
at the end of the URL with the CIK you want to resolve.
Example: https://mapping-api.herokuapp.com/cik/0001318605
Response:
[
{
"cik": "0001318605",
"ticker": "TSLA",
"name": "Tesla Motors Inc",
"sic": "3711",
"irs": "912197729"
}
]
Removing trailing 0
from the CIK also works. Instead of using 0001318605
,
you can use 1318605
. Same result.
Resolve by Ticker
Request: GET https://mapping-api.herokuapp.com/ticker/:ticker
Replace :ticker
at the end of the URL with the ticker you want to resolve.
Example: https://mapping-api.herokuapp.com/ticker/tsla
Response:
[
{
"cik": "0001318605",
"ticker": "TSLA",
"exchange": "NASDAQ",
"name": "Tesla Motors Inc",
"sic": "3711",
"irs": "912197729"
},
{
"cik": "0000863456",
"ticker": "WTSLA",
"exchange": "",
"name": "Wet Seal Inc",
"sic": "5621",
"irs": "330415940"
}
]
Two companies are returned because WTSLA
contains tsla
. The API uses regular expressions under the hood allowing complex search queries. If you only want to retrieve exact matches, then use ^
as prefix, and $
as suffix. For example, ^tsla&
(see below).
Example (exact match): GET https://mapping-api.herokuapp.com/ticker/^tsla&
Response:
[
{
"cik": "0001318605",
"ticker": "TSLA",
"exchange": "NASDAQ",
"name": "Tesla Motors Inc",
"sic": "3711",
"irs": "912197729"
}
]
Resolve by Name
Request: GET https://mapping-api.herokuapp.com/name/:name
Replace :name
at the end of the URL with the company name you want to resolve.
Example: https://mapping-api.herokuapp.com/name/Tesla
Response:
[
{
"cik": "0001318605",
"ticker": "TSLA",
"exchange": "NASDAQ",
"name": "Tesla Motors Inc",
"sic": "3711",
"irs": "912197729"
}
]
Providing Tesla Motors
as name returns the same result. You can use regular expressions here as well.
List Companies by Exchange
Request: GET https://mapping-api.herokuapp.com/exchange/:exchange
Replace :exchange
at the end of the URL with the exchange you are looking for, e.g. NASDAQ, or NYSE.
You can use regular expressions to show companies listed on different exchanges. For example, if you want to list all companies listed on NASDAQ and NYSE, you can use https://mapping-api.herokuapp.com/exchange/NASDAQ|NYSE
Example: https://mapping-api.herokuapp.com/exchange/NASDAQ
Response:
[
{
"cik": "0001099290",
"ticker": "AAC",
"name": "Sinocoking Coal & Coke Chemical Industries Inc",
"sic": "3312",
"exchange": "NASDAQ",
"irs": "593404233"
},
{
"cik": "0000006201",
"ticker": "AAL",
"name": "American Airlines Group Inc",
"sic": "4512",
"exchange": "NASDAQ",
"irs": "751825172"
},
{
"cik": "0000008177",
"ticker": "AAME",
"name": "Atlantic American Corp",
"sic": "6311",
"exchange": "NASDAQ",
"irs": "581027114"
},
// cut for brevity
]
List Companies by SIC
Request: GET http://mapping-api.herokuapp.com/sic/:sic
Replace :sic
at the end of the URL with the SIC you are looking for.
Example: http://mapping-api.herokuapp.com/sic/3711
Response:
[
{
"cik": "0001425287",
"ticker": "AMPD",
"name": "Amp Holding Inc",
"sic": "3711",
"exchange": "OTCBB",
"irs": "261394771"
},
{
"cik": "0000791115",
"ticker": "CIGI",
"name": "Coach Industries Group Inc",
"sic": "3711",
"exchange": "",
"irs": "911942841"
},
{
"cik": "0000021759",
"ticker": "COLL",
"name": "Collins Industries Inc",
"sic": "3711",
"exchange": "",
"irs": "430985160"
},
// cut for brevity...
]
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$\begingroup$ This is (almost) perfect. One defect that I found is searching with exchange does not return all (present and past) companies: mapping-api.herokuapp.com/cik/1288776 returns google mapping-api.herokuapp.com/exchange/NASDAQ does not list google $\endgroup$ Apr 22, 2020 at 3:50
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Like Jan, I've worked on putting this into an API:
https://api.odie.app/companies
The background to this, and one of the "easiest" ways to get this data from the SEC Form 4 filings as this contains the CIK of the receiver (a person) and the CIK of the issuer as well as issuer ticker:
<ownershipDocument>
<schemaVersion>X0306</schemaVersion>
<documentType>4</documentType>
<periodOfReport>2014-10-01</periodOfReport>
<notSubjectToSection16>0</notSubjectToSection16>
<issuer>
<issuerCik>0001179929</issuerCik>
<issuerName>MOLINA HEALTHCARE INC</issuerName>
<issuerTradingSymbol>MOH</issuerTradingSymbol>
</issuer>
<reportingOwner>
<reportingOwnerId>
<rptOwnerCik>0001572056</rptOwnerCik>
<rptOwnerName>James Steven</rptOwnerName>
</reportingOwnerId>
<reportingOwnerAddress>
<rptOwnerStreet1>300 UNIVERSITY AVENUE</rptOwnerStreet1>
<rptOwnerStreet2>SUITE 100</rptOwnerStreet2>
<rptOwnerCity>SACRAMENTO</rptOwnerCity>
<rptOwnerState>CA</rptOwnerState>
<rptOwnerZipCode>95825</rptOwnerZipCode>
<rptOwnerStateDescription></rptOwnerStateDescription>
</reportingOwnerAddress>
<reportingOwnerRelationship>
<isDirector>1</isDirector>
<isOfficer>0</isOfficer>
<isTenPercentOwner>0</isTenPercentOwner>
<isOther>0</isOther>
</reportingOwnerRelationship>
</reportingOwner>
I'm currently pulling in the 3.7 million documents to get a full list of mappings (the data is 50% imported after 4 days from the SEC).
The API definition (WIP) is here: https://odie.app/models and the Swagger definition is here: https://api.odie.app/spec
Hope this helps
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$\begingroup$ Could not access.
NET::ERR_CERT_AUTHORITY_INVALID
plus it's HSTS so I can't bypass it. $\endgroup$ Dec 4, 2019 at 8:04 -
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$\begingroup$ Your site doesn't work, frozen and doesn't load $\endgroup$– AzmisovAug 2, 2021 at 18:55
You can try this endpoint:
https://sec.report/Ticker/XXXX
where XXXX is the ticker you are interested in.
i.e.
https://sec.report/Ticker/AAPL
or click here: https://sec.report/Ticker/AAPL
Yes, you can access a list of CIK (Central Index Key) codes for all registered companies with the SEC through the EDGAR (Electronic Data Gathering, Analysis, and Retrieval) system. Here's how you can do it:
Go to the SEC's EDGAR company filings website: https://www.sec.gov/edgar/searchedgar/companysearch.html
Scroll down to the "Company Name" section and click on "CIK Lookup" link.
You will be redirected to the "CIK Lookup" page where you can download a complete list of CIK codes in a zip file format. Click on the "CIK Lookup Data" link to download the file.
Extract the files from the zip file and open the "cik.txt" file in a text editor. This file contains a list of all CIK codes for all registered companies with the SEC.
Note that the list of CIK codes may be large and may take some time to download and open. Also, note that the list may not include newly registered companies or companies that have recently deregistered or gone bankrupt.
OK, here is one more way. The SEC has this handy link:
https://www.sec.gov/files/company_tickers_exchange.json
The JSON query will return a list of ALL exchange traded equity securities (NYSE, NAS, OTC) with four elements: CIK, Name, Ticker, Exchange. Save the results to .TXT file and import that to Excel using the Data tab. My result was about 65,000 lines long.
Move down about ten rows to the start of the data stream, and once there a new record will start every seventh row. Use Excel functions to rearrange the vertical text to rows, and to clean up quotation marks and commas if you need to get rid of those. Some tickers come with warrants, units, or rights and you may need to segregate those depending on what you are doing. If you know Excel text functions the whole job takes about ten minutes to set up and after than you can just paste in new results from the JSON script and recalculate.
It is not clear how up to date this list is but haven't found anything missing, and it includes companies that only started trading in the past 60 days or so. If it is not actually real time, it is darn close.