Dear All,
We made these main improvements to Imported Factors
- Ability to set a “Max Days” age that automatically turns your signal to NA if it’s too old.
- Additional API endpoint to get the imported factor id via name.
- Added useful Google Colab examples.
About Imported Factors
You can upload your own signals and access them in any formula for screening, ranking and backtesting. Each factor is independently managed and updated and each data-point consists of date, stock id, and value.
Use Cases
Import an ETF’s historical holdings (by assigning the value 1 to held tickers), the executive compensation of companies, or alternative data sources for adjusted EBITDA if you can get it. You can upload the historical Zacks ranks of companies (if you can get that) to see how well they’d backtest. If you can get satellite images of parking lots, you can upload the number of shoppers visiting public retail companies.
You can read more in our knowledge base article Imported Stock Factors. If you are importing a lot of data points (millions) we strongly recommend using our API and API functions. See this article API functions: Stock Factors for links to ready to use examples like how to easily import a table of signals. Once you try the API you will not go back!
Imported Factors Properties:
- The most recent value is used from the analysis date (or as-of-date).
- You can set a maximum age for a factor so that old values become N/A.
- Your factors will be listed reference section for easy access.
- You can share your factors in a group with others.
Data Limits
Imported Factors are not designed for "big data". There's a hard limit for each account of 100M data points in total. We are working on solutions to allow you to import large datasets as well as linking your cloud datasets (like Snowflake) for unlimited number of data points.
Your feedback is always appreciated.
Thank You.