FE-Analyst

Stock & company analysis platform for investment decision-making. Built entirely on free data sources and open-source tools.

What It Does

• Full stock analysis with composite scoring (0-100) and buy/sell/hold recommendations
• Fundamental analysis - financial health, growth profile, key ratios from SEC filings
• Technical analysis - 15+ indicators (RSI, MACD, Bollinger Bands, moving averages, etc.)
• Valuation models - DCF, comparable company analysis
• Sentiment analysis - financial news (FinBERT), Reddit/social, analyst consensus
• Risk metrics - volatility, beta, Sharpe ratio, VaR, max drawdown
• Stock screening - pre-built screens (value, growth, momentum, dividend) + custom filters
• Macro dashboard - FRED economic data, Treasury yields, key indicators
• Report generation - markdown and JSON reports with full breakdown

Quick Start

# 1. Clone and setup
git clone <your-repo-url>
cd FE-analyst
chmod +x setup.sh && ./setup.sh

# 2. Activate environment
source venv/bin/activate

# 3. Add your API keys
# Edit .env (copied from .env.example during setup)

# 4. Run
python main.py analyze AAPL
python main.py compare AAPL MSFT GOOGL
python main.py screen value
python main.py quote TSLA
python main.py fundamentals NVDA
python main.py risk AMZN
python main.py macro

CLI Commands

Command	Description	Example
analyze	Full report with composite score	python main.py analyze AAPL
compare	Side-by-side comparison	python main.py compare AAPL MSFT GOOGL
screen	Stock screener (value/growth/momentum/dividend)	python main.py screen value
quote	Real-time price quote	python main.py quote TSLA
fundamentals	Key financial ratios	python main.py fundamentals NVDA
risk	Risk analysis	python main.py risk AMZN
macro	Economic indicators snapshot	python main.py macro

Project Structure

FE-analyst/
├── main.py                     # CLI entry point
├── setup.sh                    # One-command environment setup
├── requirements.txt            # Python dependencies
├── .env.example                # API key template
├── configs/
│   └── settings.yaml           # App configuration
├── src/
│   ├── config.py               # Central config loader
│   ├── data_sources/           # Data fetching clients
│   │   ├── market_data.py      # Price/OHLCV (yfinance, finnhub)
│   │   ├── fundamentals.py     # Financials, ratios (yfinance, simfin)
│   │   ├── sec_filings.py      # SEC EDGAR (edgartools)
│   │   ├── news_sentiment.py   # News + FinBERT sentiment
│   │   ├── macro_data.py       # FRED, Treasury, World Bank
│   │   ├── alternative_data.py # Reddit, insider trades, analysts
│   │   └── screener.py         # Finviz stock screener
│   ├── analysis/               # Analysis engines
│   │   ├── technical.py        # Technical indicators & signals
│   │   ├── fundamental.py      # Financial health scoring
│   │   ├── valuation.py        # DCF, comparables
│   │   ├── sentiment.py        # Multi-source sentiment aggregation
│   │   ├── risk.py             # Volatility, VaR, beta, drawdown
│   │   └── scoring.py          # Composite scorer (0-100)
│   ├── reports/
│   │   └── generator.py        # Markdown/JSON report output
│   └── utils/
│       ├── cache.py            # File-based response caching
│       ├── rate_limiter.py     # API rate limit management
│       └── logger.py           # Logging setup
├── data/
│   ├── raw/                    # Raw downloaded data
│   ├── cache/                  # Cached API responses
│   └── processed/              # Processed datasets
├── notebooks/
│   └── 01_quick_start.ipynb    # Interactive exploration
├── reports/output/             # Generated reports
├── models/                     # ML model artifacts (FinBERT cache)
├── tests/                      # Test suite
└── configs/
    └── settings.yaml           # Configuration

Data Sources (All Free)

Source	Data	Python Package
yfinance	Prices, financials, holders	yfinance
Finnhub	Quotes, news, peers, insider trades	finnhub-python
SEC EDGAR	10-K, 10-Q, 8-K filings, XBRL	edgartools
FRED	800K+ economic series	fredapi
SimFin	Bulk fundamental data	simfin
Finviz	Stock screening (90+ filters)	finvizfinance
FinBERT	Financial sentiment NLP	transformers
Reddit (PRAW)	Social sentiment	praw
World Bank	Global macro indicators	wbdata
pandas-ta	150+ technical indicators	pandas_ta

API Keys (Free Registration)

Edit .env after running setup. All keys are free tier:

1. Finnhub (most important) - https://finnhub.io/
2. FRED - https://fred.stlouisfed.org/docs/api/api_key.html
3. SimFin - https://simfin.com/
4. FMP - https://financialmodelingprep.com/
5. Reddit - https://www.reddit.com/prefs/apps
6. SEC EDGAR - No key needed, just set your email as user-agent

The platform works with partial keys - it gracefully degrades if a source is unavailable.

Scoring System

The composite score (0-100) weights five dimensions:

Dimension	Weight	What It Measures
Fundamental	30%	Financial health, ROE, debt, margins
Valuation	25%	DCF intrinsic value vs. current price
Technical	20%	RSI, MACD, moving average signals
Risk	15%	Volatility, beta, drawdown
Sentiment	10%	News, social media, analyst consensus

Recommendation thresholds: 75+ Strong Buy, 60+ Buy, 45+ Hold, 30+ Sell, <30 Strong Sell

Disclaimer

This tool is for informational and educational purposes only. It is not financial advice. Always conduct your own research and consult with qualified financial advisors before making investment decisions.