These are the objects you will get back with each call to the Alpha News Stream API, providing the schema you can use to integrate into your applications.
- status (string) – The outcome of the news API request (Success or Error).
- message (string) – The accompanying message for response. If there is an error, this field will contain a plain language message explaining the error.
- delay (number) – How long the response took, in seconds.
- articles (array) –
- pub_time (string) – The publication time of article, specified in seconds since January 1, 1970.
- headline (string) – The headline for the article.
- date (string) – The date of the article. Specified as MM/DD/YYYY where MM and DD may be one or two digits.
- time (string) – The time of the article. Specified as HH:MM AM or PM. HH may be one or two digits.
- source (string) – The source of the article, whether a news or press release source.
- url (string) – The URL of the article.
- images (string) – The URL for included article image (for research use only).
- tags (array) –
- id (string) – The unique id for the article.
- summary (string) – A summary of the article; its first 300 characters (for research use only).
- paywall (string) – Indicates type of paywall (only present when paywall_notification=on). Values are None, Soft, or Hard.
- symbols (array) – Symbol tags for the article. Symbol format in the output is EXCHANGE:TICKER where the EXCHANGE prefix is in MIC (ISO 10383) format. (Please note that this format is different than the input parameter format TICKER.EXCHANGE, where the EXCHANGE is a suffix.)
- sectors (array) – Sector tags for the article.
- subsectors (array) – Subsector tags for the article.
- companies (array) – Company tags for the article.
- topics (array) – Topic tags for the article.
- category_tags (array) – Category tags for the article.
The schema can be used to generate integration code, and do most of the heavy lifting when decoding the response from the ANS API.
Data Points (Objects)
The list below shows objects we add to each news headline when available or applicable. Press releases will typically include fewer data points.
These are tag(s) we add, where possible, to identify company ticker symbols for the following exchanges: NYSE, NASDAQ, TSX, and the LSE’s FT100 stocks. The symbols field that you get back with each call to the API will include the exchange prefix in ISO 10383 format (XNYS, XNAS, XTSE and XLON, respectively). An example is: “XNYS:IBM”. Not every article will include these tags. (Symbol format in the output is EXCHANGE:TICKER whereas input parameter format is TICKER.EXCHANGE). Not every article will include a symbols tag.
These are tag(s) we add when a symbol tag is present based on the symbols above. It identifies the company’s industry sector as defined by the exchange. This is distinct from the category_tags; outlined below. Most, but not all, symbols-identified articles will include this tag. The most commonly used sector designations include:
These are tag(s) we add, when a symbol tag is present based on the symbols, above. It identifies the company’s industry subsector as defined by the exchange. It includes many potential parameters for companies public or private, so there is no list of all possible parameters. Most, but not all, symbols-identified articles will include this tag.
companies Company names within an article may be listed here.
The above tag is semantically generated and includes many potential parameters for companies public or private, so there is no list of all possible parameters. Not every article will include these tags.
images Includes the link to an associated image within the RSS newsfeed.
The above data point adds a link, where available, to an image included in the RSS newsfeed content that appears in the originating article. Copyright applies.
paywall Designates whether the headline source has a paywall.
The above tag is generated to show whether the originating news source has a paywall for the linked article. Designations are: Hard (most or all access requires subscription or registration); Soft (articles are free to read until some article limit is reached, then subscription is required); or None (all articles are free to read)
topics Other topics, even non-financial, may be included here.
The topics tag may be found in some historical headlines. It was semantically generated based on an open source tagging add-on we no longer utilize and includes a variety of generic topics as parameters. This tag could be used to identify future data points.
These are editorial tag(s) we add to identify a specific financial category or topic. They are specific, finite and defined by our editorial team based on their usefulness. Some will overlap with sector tag parameters. Not every article will include these tags.
Some of these categories are based upon Morningstar sector designations. Category tag parameters may include:
Financial_News An editorially chosen all-purpose financial headline category.
General When no topic is specified.
Business_Video Just video.
Business_Podcast Just podcasts
Financial_Bloggers Just bloggers.
For your convenience, we have included Open API specifications:
Download Open API Specifications
Most plans have unlimited usage. Check your plan for specifics.
• Trial plan: 250 requests per day
• Custom plan: per agreement
• Burst rate limit: 1 request per second
• Editorial limit: In headlines where Summary text is available, we provide only the first 300 characters. This Summary text and the link to article images, if available, are for research use only as they are copyright-protected by the source.
• Editorial limit: Archived headlines are available back to January 1, 2017.
Streaming News (no older than 14 days): To avoid missing a headline, the best practice is to request all news, count=1000, once every 5 minutes. Once you have retrieved the headlines, you can sort or filter them as appropriate for your needs (by symbol, by source, by topic, etc.)
Archived News (any headline older than 14 days): The best practice is to request by symbol or source, count=100, with a start_date and end_date. If you are scanning a large date range, start with the most recent end_date and work backwards, adjusting the end_date to the earliest found article date, and repeat.