A professional-grade stock analysis web app built with Python and Streamlit. Analyze any stock with real-time data, AI-powered investment thesis, famous investor simulations, backtesting, and global market coverage.

🌐 Live at: smartstock.trading

• Overview — Live price chart (Webull-style candlesticks), key metrics, 52-week range, volume, dividends
• Valuation — P/E, Forward P/E, P/S, PEG, EV/EBITDA, interactive DCF fair value calculator, analyst price targets, financial statements
• Risk — Sharpe ratio, Sortino, Calmar, Max Drawdown, VaR/CVaR, Beta vs S&P 500, rolling risk metrics
• Industry — Sector comparison, peer benchmarking, industry averages
• Technical — RSI, MACD, Bollinger Bands, moving averages, volume analysis
• Comparison — Side-by-side comparison of any two stocks across 30+ metrics
• Company News — Latest news with sentiment tagging

• AI Thesis — Rule-based AI investment thesis with bull/bear case, factor scores, ESG assessment, catalysts and risks
• Investor View — Simulate portfolios of famous investors (Buffett, Dalio, Lynch, Ackman, and more) with:
  • Live factor scoring (Quality, Value, Growth, Momentum, Stability)
  • Market regime detection (VIX, SPY/QQQ/IWM breadth)
  • News shock overlay
  • Full backtest engine with SPY benchmark comparison
  • Monthly returns heatmap, rolling Sharpe, return distribution
  • Alpha, Beta, R², Treynor, Omega Ratio, Ulcer Index, and more

• Market News — Global market headlines with sentiment and impact analysis
• Market Rankings — Top movers screener with AI scoring across global markets
• Global Indexes — World market overview across all continents
• Commodities — Oil, gold, silver, natural gas, and more

• Bond Calculator — Yield to maturity, duration, convexity, cashflow table
• Option Calculator — Black-Scholes pricing with full Greeks (Delta, Gamma, Theta, Vega, Rho)

1. Clone the repo

git clone https://github.com/ym3642/stock_analyzer.git
cd stock_analyzer

2. Create a virtual environment

python -m venv venv
venv\Scripts\activate        # Windows
source venv/bin/activate     # Mac/Linux

3. Install dependencies

pip install -r requirements.txt

4. Run the app

streamlit run app.py

Open your browser at http://localhost:8501

The app is deployed on Render with automatic deploys from this GitHub repo.

Every git push to main triggers a redeploy automatically:

Local code  →  git push  →  GitHub  →  Render auto-deploy  →  smartstock.trading

stock_analyzer/
├── app.py              # Main application (all-in-one)
├── Procfile            # Render/Railway start command
├── requirements.txt    # Python dependencies
└── README.md           # This file

SmartStock is for educational and informational purposes only. Nothing on this platform constitutes financial advice. Always conduct your own due diligence and consult a qualified financial advisor before making investment decisions. Data is sourced from Yahoo Finance and may be delayed or inaccurate.

MIT