findata-toolkit-us
Financial data toolkit for US market analysis. Provides scripts to fetch real-time stock data (yfinance), SEC filings and insider trades (EDGAR), financial statement calculators (DuPont, Z-Score, M-Score, F-Score), portfolio analytics (VaR, stress testing, health scoring), multi-factor screening, and macro indicators (FRED). Use when you need live US market data to ground investment analysis. All data sources are free — no API keys required.
What this skill does
# FinData Toolkit — US Market A self-contained data toolkit providing live financial data and quantitative calculations for US market analysis. All data sources are **free** and require **no API keys**. ## Setup Install dependencies (one-time): ```bash pip install -r requirements.txt ``` ## Available Tools All scripts are in the `scripts/` directory. Run from the skill root directory. ### 1. Stock Data (`scripts/stock_data.py`) Fetch stock fundamentals, price history, and financial metrics via yfinance. | Command | Purpose | |---------|---------| | `python scripts/stock_data.py AAPL` | Basic company info | | `python scripts/stock_data.py AAPL --metrics` | Full financial metrics (valuation, profitability, leverage, growth, analyst consensus) | | `python scripts/stock_data.py AAPL --history --period 1y` | OHLCV price history | | `python scripts/stock_data.py AAPL --financials` | Income statement, balance sheet, cash flow | | `python scripts/stock_data.py AAPL MSFT GOOGL --screen` | Screen stocks against value filters | ### 2. SEC EDGAR (`scripts/sec_edgar.py`) Fetch insider trading data (Form 4), company filings, and CIK lookups. | Command | Purpose | |---------|---------| | `python scripts/sec_edgar.py insider AAPL` | Recent insider trades | | `python scripts/sec_edgar.py insider AAPL --days 90` | Insider trades in last 90 days | | `python scripts/sec_edgar.py filings AAPL --form-type 10-K` | Recent 10-K filings | | `python scripts/sec_edgar.py cik AAPL` | Look up CIK number | ### 3. Financial Calculators (`scripts/financial_calc.py`) DuPont decomposition, Altman Z-Score, Beneish M-Score, Piotroski F-Score, earnings quality, and working capital analysis. | Command | Purpose | |---------|---------| | `python scripts/financial_calc.py AAPL --all` | All calculations | | `python scripts/financial_calc.py AAPL --dupont` | 5-factor DuPont decomposition | | `python scripts/financial_calc.py AAPL --zscore` | Altman Z-Score (bankruptcy risk) | | `python scripts/financial_calc.py AAPL --mscore` | Beneish M-Score (manipulation detection) | | `python scripts/financial_calc.py AAPL --fscore` | Piotroski F-Score (financial strength) | | `python scripts/financial_calc.py AAPL --quality` | Earnings quality assessment | | `python scripts/financial_calc.py AAPL --working-capital` | Working capital & CCC analysis | ### 4. Portfolio Analytics (`scripts/portfolio_analytics.py`) Portfolio risk analysis: concentration, correlation clusters, VaR/CVaR, stress testing, and health scoring. | Command | Purpose | |---------|---------| | `python scripts/portfolio_analytics.py --holdings "AAPL:30,MSFT:25,GOOGL:20,AMZN:15,META:10"` | Full health score (0–100) | | `... --concentration` | Concentration analysis (HHI, sector) | | `... --correlation` | Correlation clusters & EDR | | `... --risk` | VaR/CVaR, Sharpe, Sortino, beta | | `... --stress` | Historical stress testing (5 scenarios) | ### 5. Factor Screener (`scripts/factor_screener.py`) Multi-factor stock scoring: value, momentum, quality, low volatility, size, growth. | Command | Purpose | |---------|---------| | `python scripts/factor_screener.py --universe "AAPL,MSFT,GOOGL,AMZN" --top 5` | Screen custom universe | | `python scripts/factor_screener.py --sp500-sample --top 10` | Screen S&P 500 sample | | `... --factors value,quality` | Use specific factors only | ### 6. Macro Data (`scripts/macro_data.py`) US macroeconomic indicators from FRED. | Command | Purpose | |---------|---------| | `python scripts/macro_data.py --dashboard` | Full macro dashboard | | `python scripts/macro_data.py --rates` | Interest rates & yield curve | | `python scripts/macro_data.py --inflation` | CPI, PCE, breakevens | | `python scripts/macro_data.py --gdp` | GDP & leading indicators | | `python scripts/macro_data.py --employment` | Unemployment, payrolls, JOLTS | | `python scripts/macro_data.py --cycle` | Business cycle phase assessment | ## Data Sources | Source | Data | API Key | |--------|------|---------| | Yahoo Finance (yfinance) | Stock quotes, financials, history | Not required | | SEC EDGAR | Filings, insider trades (Form 4) | Not required | | FRED | Macro indicators | Not required | ## Output Format All scripts output **JSON to stdout** for easy parsing. Errors go to stderr. ## Configuration Optional: Edit `config/data_sources.yaml` to customize rate limits or add API keys for premium data sources.
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