Employee Flow Event Engine — Researching Employee Stock Purchase Plan Events

The Employee Flow Event Engine is a Python research framework I developed to investigate Employee Stock Purchase Plan (ESPP) events using evidence from SEC filings.

The goal is to turn potentially ambiguous filing information into structured, reviewable research data.

The system focuses on:

• Event identification: Extracting potential ESPP purchase dates from filing evidence.
• Validation and review: Distinguishing accepted, corrected, rejected, and unreviewed events.
• Research integration: Producing validated event-study observations while preserving source information and uncertainty.

The demonstration uses synthetic TestCo filing examples and runs them through the engine’s actual processing pipeline.

An important feature is that only appropriately reviewed events enter the validated research dataset. Missing or uncertain evidence isn’t automatically treated as a confirmed event.

GitHub: https://github.com/rossautomatedsolutions/employee_flow_event_engine

Research and demonstration purposes only. Not investment advice.