How I Built a System to Track Insider Trading Data with Python
The article explains how to build a Python system that pulls, cleans, and stores insider trading data from SEC filings automatically.
Why it matters
Tracking insider trading data can provide valuable insights for investors, as it offers a window into the confidence and expectations of company insiders.
Key Points
- 1Insider trading data refers to the buying and selling activity of company insiders, which is publicly available
- 2Tracking insider transactions can provide valuable insights for investors, as studies show stocks with heavy insider buying outperform the market
- 3The author built a Python script that fetches insider trading data from the FMP API, cleans and deduplicates the data, and saves it to a PostgreSQL database
Details
The article walks through the process of building a Python system to track insider trading data. Insider trading data refers to the buying and selling activity of company insiders, including CEOs, CFOs, board members, and major shareholders. This data is publicly available through SEC filings, but can be difficult for retail investors to access and analyze. The author explains that when insiders buy shares with their own money, it often signals confidence in the company's future, and studies show these stocks tend to outperform the market. The Python script the author built fetches insider trading data from the FMP API, cleans and deduplicates the data, and saves it to a PostgreSQL database. This allows the author to easily track and analyze insider trading activity to make more informed investment decisions.
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