In Apperate, you can refer to an equity symbol using any supported financial identifier type. Apperate relates equivalent symbols across different identifier types. You can, for example, use a CUSIP symbol to query datasets that store symbols in ISIN, FIGI, or another supported identifier type. Apperate, in effect, normalizes the financial identifiers.
Subscribing to the financial identifier data would cost you tens of thousands of dollars annually. Implementing a mapping between the identifiers is complicated and time-consuming. We’ve normalized all this for you so you can concentrate on business logic for serving your customers.
Here we’ll demonstrate two things:
Querying normalized datasets
Joining normalized datasets
Querying Normalized Datasets#
The following dataset’s
symbol column refers to Apple using the
US0378331005 ISIN symbol.
You can, however, query on the dataset’s Apple data by refering to Apple using any supported financial identifier type. For example, you can query the dataset using the ISIN symbol
In Apperate, you can query the dataset using any supported financial identifier type. Here is a SQL query and HTTP request that use the INET symbol
AAPL to query for Apple data.
SELECT * FROM MY.`AAPL_ISIN` a where a.symbol='AAPL';
REST API URL:
REST API URL Response:
You can similarly join datasets on equivalent symbols.
Joining Normalized Datasets#
You can, for example, create a view of Apple high, open, low, close data and corporate details by joinging this AAPL_ISIN dataset with the Core COMPANY dataset. Here’s the SQL.
SELECT ceo, companyName, city, a.date, open, close, high, low, volume, ceo, companyName, city FROM MY.`AAPL_ISIN` a JOIN core.`COMPANY` c ON c.symbol = a.symbol WHERE a.symbol = 'AAPL';
WHERE clauses and ON clauses must only operate on indexed properties (columns). See the Unique Index components here.
You can then create a view from the results by clicking Create view. Voila! You’re view dataset is available to use like any other dataset.