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):
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.
1---2name: findata-toolkit-us3description: 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.4license: Apache-2.05---67# FinData Toolkit — US Market89A 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**.1011## Setup1213Install dependencies (one-time):1415```bash16pip install -r requirements.txt17```1819## Available Tools2021All scripts are in the `scripts/` directory. Run from the skill root directory.2223### 1. Stock Data (`scripts/stock_data.py`)2425Fetch stock fundamentals, price history, and financial metrics via yfinance.2627| Command | Purpose |28|---------|---------|29| `python scripts/stock_data.py AAPL` | Basic company info |30| `python scripts/stock_data.py AAPL --metrics` | Full financial metrics (valuation, profitability, leverage, growth, analyst consensus) |31| `python scripts/stock_data.py AAPL --history --period 1y` | OHLCV price history |32| `python scripts/stock_data.py AAPL --financials` | Income statement, balance sheet, cash flow |33| `python scripts/stock_data.py AAPL MSFT GOOGL --screen` | Screen stocks against value filters |3435### 2. SEC EDGAR (`scripts/sec_edgar.py`)3637Fetch insider trading data (Form 4), company filings, and CIK lookups.3839| Command | Purpose |40|---------|---------|41| `python scripts/sec_edgar.py insider AAPL` | Recent insider trades |42| `python scripts/sec_edgar.py insider AAPL --days 90` | Insider trades in last 90 days |43| `python scripts/sec_edgar.py filings AAPL --form-type 10-K` | Recent 10-K filings |44| `python scripts/sec_edgar.py cik AAPL` | Look up CIK number |4546### 3. Financial Calculators (`scripts/financial_calc.py`)4748DuPont decomposition, Altman Z-Score, Beneish M-Score, Piotroski F-Score, earnings quality, and working capital analysis.4950| Command | Purpose |51|---------|---------|52| `python scripts/financial_calc.py AAPL --all` | All calculations |53| `python scripts/financial_calc.py AAPL --dupont` | 5-factor DuPont decomposition |54| `python scripts/financial_calc.py AAPL --zscore` | Altman Z-Score (bankruptcy risk) |55| `python scripts/financial_calc.py AAPL --mscore` | Beneish M-Score (manipulation detection) |56| `python scripts/financial_calc.py AAPL --fscore` | Piotroski F-Score (financial strength) |57| `python scripts/financial_calc.py AAPL --quality` | Earnings quality assessment |58| `python scripts/financial_calc.py AAPL --working-capital` | Working capital & CCC analysis |5960### 4. Portfolio Analytics (`scripts/portfolio_analytics.py`)6162Portfolio risk analysis: concentration, correlation clusters, VaR/CVaR, stress testing, and health scoring.6364| Command | Purpose |65|---------|---------|66| `python scripts/portfolio_analytics.py --holdings "AAPL:30,MSFT:25,GOOGL:20,AMZN:15,META:10"` | Full health score (0–100) |67| `... --concentration` | Concentration analysis (HHI, sector) |68| `... --correlation` | Correlation clusters & EDR |69| `... --risk` | VaR/CVaR, Sharpe, Sortino, beta |70| `... --stress` | Historical stress testing (5 scenarios) |7172### 5. Factor Screener (`scripts/factor_screener.py`)7374Multi-factor stock scoring: value, momentum, quality, low volatility, size, growth.7576| Command | Purpose |77|---------|---------|78| `python scripts/factor_screener.py --universe "AAPL,MSFT,GOOGL,AMZN" --top 5` | Screen custom universe |79| `python scripts/factor_screener.py --sp500-sample --top 10` | Screen S&P 500 sample |80| `... --factors value,quality` | Use specific factors only |8182### 6. Macro Data (`scripts/macro_data.py`)8384US macroeconomic indicators from FRED.8586| Command | Purpose |87|---------|---------|88| `python scripts/macro_data.py --dashboard` | Full macro dashboard |89| `python scripts/macro_data.py --rates` | Interest rates & yield curve |90| `python scripts/macro_data.py --inflation` | CPI, PCE, breakevens |91| `python scripts/macro_data.py --gdp` | GDP & leading indicators |92| `python scripts/macro_data.py --employment` | Unemployment, payrolls, JOLTS |93| `python scripts/macro_data.py --cycle` | Business cycle phase assessment |9495## Data Sources9697| Source | Data | API Key |98|--------|------|---------|99| Yahoo Finance (yfinance) | Stock quotes, financials, history | Not required |100| SEC EDGAR | Filings, insider trades (Form 4) | Not required |101| FRED | Macro indicators | Not required |102103## Output Format104105All scripts output **JSON to stdout** for easy parsing. Errors go to stderr.106107## Configuration108109Optional: Edit `config/data_sources.yaml` to customize rate limits or add API keys for premium data sources.
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