Companies use reported ownership data to understand the composition of their shareholder base and identify changes that may warrant further investigation. This notebook demonstrates a programmatic workflow using the LSEG Data Library for Python: retrieve two period-end ownership snapshots for an issuer, compare reported positions, and produce a concise investor watchlist.
The workflow:
- Opens an LSEG Data Library session using LSEG Workspace access.
- Retrieves the latest two quarterly or monthly ownership snapshots for a selected company.
- Checks that the response is complete before comparing the periods.
- Identifies material increases, material reductions, newly reported positions, and positions no longer represented.
- Ranks the flagged investors by materiality and reporting recency.
- Presents the results in a compact watchlist suitable for analyst review, reporting, dashboards, or alerts.
The notebook is a monitoring and operationalization example, not a transaction feed, trading strategy, or stock-performance forecast. It compares reported ownership snapshots and does not infer trade dates, investor intent, or a confirmed sale when an investor is no longer represented. The thresholds and review cadence can be adapted to the issuer and the needs of the analyst or team using the workflow.
Details and concepts are further explained in the Who Owns Your Company, and What Has Changed? article published on the LSEG Developer Community portal.
The source code presented in this project has been written by LSEG only for the purpose of illustrating the concepts of creating example scenarios using the LSEG Data Library for Python.
Note: To ask questions and benefit from the learning material, I recommend you to register on the LSEG Developer Community
To execute the workbook, refer to the following:
License(s):
- Permissions and API access to Ownership data
- Tested with Python 3.12.14
- Packages: lseg-data and pandas
- LSEG Data Library for Python installation: 'pip install lseg-data'
The package includes a single Jupyter Notebook, ownership_monitoring_report.ipynb, demonstrating the monitoring workflow. Users with API access to Ownership data can run the notebook through either supported session type:
-
Desktop session
Uses Ownership access provided through the LSEG Workspace desktop application.
-
Platform session
Uses Ownership access provided through the LSEG Data Platform. Configure the session and credentials according to the access available in your environment.
- Nick Zincone - Release 1.0. Initial version