findata-toolkit-us

You can fetch US market stock data without an API key by running local Python scripts that use yfinance to retrieve real-time prices, financials, and metrics, outputting JSON directly to stdout. This approach simplifies data collection for investment research.

Access SEC EDGAR filings and insider trades programmatically by executing the toolkit's Python scripts, which retrieve regulatory data from free sources and output structured JSON without requiring authentication or external API keys.

Yes, you can compute DuPont, Z-Score, M-Score, and Piotroski F-Score using free stock data fetched via yfinance, applying the toolkit's quant analytics scripts for financial metric calculations and portfolio health scoring.

Yes, you need to install pandas, numpy, scipy, pandas-datareader, yfinance, requests, tabulate, and yaml to run the Python scripts for data collection and analysis. These dependencies enable the toolkit's quantitative computations.

Pull macro indicators for US equities research by using the toolkit's scripts to retrieve data via FRED, enabling you to monitor macro context and perform multi-factor screening in a single workflow without needing paid data subscriptions.

Yes, findata-toolkit-us supports portfolio analytics including VaR, stress testing, and health scoring, applying local Python scripts to deterministic tasks for portfolio managers and analysts evaluating US equities.