institutional-flow-tracker

This Skill screens for stocks with significant institutional ownership changes by analyzing 13F filings data. You can run it using Python 3.8+ and filter results by minimum change percentage to uncover smart money patterns.

Smart money accumulation is identified by analyzing institutional investor ownership changes and portfolio flows from 13F filings. The framework uses a tier-based weighting system for institutional investors to interpret these signals based on their activity levels.

Yes, you can screen for stocks with significant institutional ownership changes using Python 3.8+. The script requires the requests library and FMP API access to filter top stocks by minimum ownership change percentages.

Yes, FMP API access is required to analyze historical institutional ownership trends, top holders, and position changes for individual stocks. You also need Python 3.8+ and the requests library installed to execute the analysis scripts.

Yes, the institutional tracking feature allows you to follow specific hedge funds or investment firms to understand their portfolio moves. It analyzes their position changes and historical ownership trends based on 13F filings data.

You interpret signals from institutional investor activity using the provided signal interpretation framework. It applies a tier-based weighting system to institutional investors to evaluate the significance of their accumulation or distribution patterns.