Problem
SEC Form 4 filings are public, but the EDGAR system is essentially a raw data dump. An attempt to prove the hypothesis that insider trading typically beat the S&P 500 was made, and proved success; however, manual parsing and analysis of data points proved time-consuming and prone to errors. Continued use of manual labor would prove inefficient and lead to losses in profit.
Solution
In conjunction with my brother, we designed, programmed, and tested a python based analysis tool. This tool parses SEC databases, conducts in-depth analysis, and returns flagged transactions. This system is an automated pipeline that continuously monitors SEC EDGAR for new Form 4 filings, parses and stores the relevant data, and then runs a multi-layered analysis to surface only the purchases most likely to be meaningful. It filters out noise such as grants, awards, and any other purchases which reflect strategic accumulation rather than personal conviction and scores what remains against a set of weighted qualifiers. The output is a ranked, scored list of insider purchases that an investor can act on with genuine context behind each signal.
Impact
The impact of this project is clear, there are several strong paths forward, each with real potential. We’re not limited to a single answer we have multiple good options to choose from. There are a countless number of independant investors most of whom would benefit from a system like this. Currently, talks of monetization systems are in progress, but nothing has been set in stone quite yet.