AI-Powered Financial Trading Analysis Platform

A comprehensive, production-ready trading intelligence platform featuring real-time market analysis, portfolio management, ML-based pattern detection, sentiment analysis, and automated alerts.

Features

Core Capabilities

• 📊 Real-Time Market Analysis: Live stock quotes, charts, and technical indicators
• 🤖 AI-Powered Insights: Local LLM integration (Ollama) for intelligent chart analysis
• 📈 Pattern Recognition: Automated detection of chart patterns (Head & Shoulders, Double Tops/Bottoms, etc.)
• 🧠 ML Pattern Detection: Machine learning-based prediction of future patterns
• 💹 Portfolio Management: Track holdings, transactions, and performance metrics
• 📰 News Integration: Real-time financial news with sentiment analysis
• ⚡ Volatile Stocks Scanner: Track top movers, volume leaders, and high-momentum stocks (174+ symbols)
• 🎯 Smart Alerts: Customizable price, volume, and technical indicator alerts
• 👥 Politician Trade Tracking: Monitor and copy trades from congressional filings
• 📊 Options Analysis: Advanced options Greeks and strategy analysis
• ⏰ Trading Time Analyzer: Identify optimal trading hours based on performance
• 🔗 Correlation Analysis: Find correlated assets for diversification
• 📝 Trade Journal: Document and analyze your trading decisions
• 🗓️ Market Calendar: Track earnings, dividends, and economic events

Technical Features

• Cryptocurrency Support: Monitor 24 major cryptos alongside stocks
• Custom Watchlists: Create and manage multiple watchlists
• Session Persistence: SQLite database with user authentication
• Google OAuth: Secure login with Google accounts
• Responsive UI: Modern, mobile-friendly interface
• RESTful API: Comprehensive API for programmatic access
• Production Ready: Docker + Kubernetes deployment configurations

Architecture

Backend Stack

• Framework: Flask 3.0
• Database: SQLAlchemy with SQLite (easily upgradable to PostgreSQL)
• Data Sources: yfinance, Alpha Vantage, News API, Quandl
• ML/AI: scikit-learn, statsmodels, Ollama (local LLM)
• Authentication: Flask-Login, Authlib (Google OAuth)
• Charting: Plotly, mplfinance, matplotlib
• Production Server: Gunicorn with worker processes

Frontend Stack

• HTML5/CSS3: Modern semantic markup
• Vanilla JavaScript: No framework dependencies
• Responsive Design: Mobile-first approach
• Real-time Updates: AJAX for live data

Quick Start

Local Development

# Clone repository
git clone https://github.com/yourusername/trader-tools.git
cd trader-tools

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.template .env
# Edit .env with your API keys and settings

# Initialize database
python -c "from db_config import init_database; from flask import Flask; app = Flask(__name__); init_database(app)"

# Run application
python app.py

Access at http://localhost:5000

Docker

# Build image
docker build -t trader-tools .

# Run container
docker run -p 5000:5000 --env-file .env trader-tools

Production Kubernetes Deployment

🚀 No Docker? Start Here: NO_DOCKER_QUICKSTART.md - Deploy using GitHub Actions (easiest!)

📋 For Production MicroK8s Cluster: See PRODUCTION.md for deploying to existing production MicroK8s cluster.

�📘 Full Deployment Guide: See DEPLOYMENT.md for comprehensive deployment documentation.

⚡ Quick Reference: See QUICKSTART.md for command reference.

Deployment Methods:

• Production MicroK8s + ArgoCD: GitOps deployment to existing cluster - PRODUCTION.md
• Helm Chart: Recommended for production - helm/trader-tools
• Kustomize: Lightweight overlay configuration - k8s/
• Raw Manifests: Direct Kubernetes YAMLs - k8s/
• ArgoCD GitOps: Automated sync and self-healing - argocd/

Quick examples:

Helm:

# Update image registry in values.yaml first
helm install trader-tools ./helm/trader-tools \
  --set image.repository=docker.io/yourusername/trader-tools \
  --set-string secrets.secretKey="your-secret" \
  --set-string secrets.googleClientId="your-client-id" \
  --set-string secrets.googleClientSecret="your-secret"

Production ArgoCD (for existing MicroK8s cluster):

# 1. Edit argocd/application.yaml with your Git repo and registry
# 2. Push code to Git
# 3. Create secrets on cluster
kubectl create secret generic trader-tools-secret \
  --from-literal=SECRET_KEY='your-secret' \
  --namespace trader-tools

# 4. Deploy
kubectl apply -f argocd/application.yaml

Configuration

Required Environment Variables

# Flask Configuration
SECRET_KEY=your-strong-random-secret-key
FLASK_ENV=production

# Google OAuth (Required for authentication)
GOOGLE_CLIENT_ID=your-google-client-id.apps.googleusercontent.com
GOOGLE_CLIENT_SECRET=your-google-client-secret

# Database
DATABASE_URL=sqlite:///instance/financial_analysis.db

# Optional API Keys (enhance functionality)
ALPHA_VANTAGE_API_KEY=your-alpha-vantage-key
NEWS_API_KEY=your-news-api-key
QUANDL_API_KEY=your-quandl-api-key

# LLM Configuration
OLLAMA_BASE_URL=http://localhost:11434

Getting API Keys

• Google OAuth: Google Cloud Console
• Alpha Vantage: alphavantage.co
• News API: newsapi.org
• Quandl: data.nasdaq.com
• Ollama: ollama.ai - Free local LLM

Project Structure

trader-tools/
├── app.py                         # Main Flask application
├── models.py                      # Database models
├── config.py                      # Configuration management
├── requirements.txt               # Python dependencies
├── Dockerfile                     # Container image definition
├── .dockerignore                  # Docker build exclusions
│
├── .github/                      # GitHub Actions CI/CD
│   └── workflows/
│       ├── build.yml             # Docker Hub build
│       ├── build-ghcr.yml        # GitHub Container Registry build
│       └── README.md
│
├── k8s/                          # Kubernetes manifests
│   ├── namespace.yaml
│   ├── deployment.yaml
│   ├── service.yaml
│   ├── ingress.yaml
│   ├── configmap.yaml
│   ├── secret.yaml.template
│   ├── pvc.yaml
│   ├── hpa.yaml
│   └── kustomization.yaml
│
├── helm/                         # Helm chart
│   └── trader-tools/
│       ├── Chart.yaml
│       ├── values.yaml
│       └── templates/
│
├── argocd/                       # ArgoCD GitOps manifests
│   ├── application.yaml          # Production app
│   ├── application-dev.yaml      # Development app
│   ├── application-kustomize.yaml
│   └── README.md
│
├── static/                       # Frontend assets
│   ├── styles.css
│   ├── app.js
│   ├── portfolio.js
│   ├── volatile_stocks.js
│   ├── copytrading.js
│   └── ...
│
├── templates/                    # HTML templates
│   ├── dashboard.html
│   ├── portfolio.html
│   └── ...
│
├── Core Modules
│   ├── data_fetcher.py              # Market data retrieval
│   ├── chart_generator.py           # Chart creation
│   ├── pattern_recognizer.py        # Technical pattern detection
│   ├── llm_analyzer.py              # LLM integration
│   ├── ml_pattern_detector.py       # ML predictions
│   ├── sentiment_analyzer.py        # News sentiment
│   ├── options_analyzer.py          # Options Greeks
│   ├── volatility_monitor.py        # Volatile stocks scanner
│   ├── portfolio_analyzer.py        # Portfolio analytics
│   ├── smart_alerts.py              # Alert engine
│   ├── politician_trades.py         # Congressional trades
│   └── ... 17 total modules
│
└── Documentation
    ├── README.md                # This file
    ├── DEPLOYMENT.md            # Comprehensive deployment guide
    ├── PRODUCTION.md            # Production MicroK8s deployment
    ├── QUICKSTART.md            # Quick command reference
    ├── NO_DOCKER_QUICKSTART.md  # Deploy without Docker installed
    └── database_schema.sql      # Database schema

API Endpoints

Market Data

• POST /analyze - Analyze a stock symbol
• GET /api/market/volatile-stocks - Top volatile stocks
• GET /api/market/fastest-movers - Biggest % movers
• GET /api/market/volume-leaders - Volume surge leaders
• GET /api/market/momentum-stocks - High momentum picks

Portfolio Management

• GET /api/portfolio - Get portfolio summary
• POST /api/portfolio/transaction - Add transaction
• GET /api/portfolio/performance - Performance metrics

Alerts & Monitoring

• GET /api/alerts - List active alerts
• POST /api/alerts - Create new alert
• GET /api/alerts/suggestions - Get AI alert suggestions

Other Features

• GET /api/watchlist - User watchlists
• GET /api/politician-trades - Recent politician trades
• GET /api/correlation - Asset correlation matrix
• GET /api/journal - Trade journal entries

See DEPLOYMENT.md for complete API documentation.

Production Deployment

Prerequisites

• Docker 20.10+
• Kubernetes 1.24+
• Helm 3.8+ (recommended)
• Container registry access

Quick Deploy with Helm

# 1. Build and push image
docker build -t your-registry/trader-tools:latest .
docker push your-registry/trader-tools:latest

# 2. Install with Helm
helm install trader-tools ./helm/trader-tools \
  --set image.repository=your-registry/trader-tools \
  --set-string secrets.secretKey="$(python -c 'import secrets; print(secrets.token_hex(32))')" \
  --set-string secrets.googleClientId="your-client-id" \
  --set-string secrets.googleClientSecret="your-client-secret"

# 3. Get the URL
kubectl get ingress -n trader-tools

Features in Production

• High Availability: 2-10 replicas with auto-scaling
• Load Balancing: Kubernetes Service with session affinity
• Persistent Storage: 10GB PVC for database
• Health Checks: Liveness and readiness probes
• SSL/TLS: Automatic certificates with cert-manager
• Monitoring: Prometheus metrics and Grafana dashboards
• Rolling Updates: Zero-downtime deployments
• Resource Management: CPU/memory requests and limits

See DEPLOYMENT.md for comprehensive production deployment guide.

Development

Running Tests

pytest
pytest --cov=. --cov-report=html

Code Style

black .
flake8 .
mypy app.py

Local LLM Setup

# Install Ollama
curl https://ollama.ai/install.sh | sh

# PDatabase Schema

The platform uses SQLAlchemy ORM with the following models:

- **User**: User accounts and profiles
- **Watchlist**: Custom stock watchlists
- **Portfolio**: Portfolio holdings
- **Transaction**: Buy/sell transactions  
- **OptionsPosition**: Options contracts
- **Alert**: Price and technical alerts
- **MLPattern**: ML pattern predictions
- **MLPrediction**: Historical predictions
- **AnalysisHistory**: Chart analysis history

See [database_schema.sql](database_schema.sql) for complete schema
| BTC-USD | Bitcoin |

**💡 Tip:** Use shortcuts like **SPX**, **DJI**, or **NASDAQ** - they're automatically mapped to the correct Yahoo Finance symbols!

**📚 For more symbols:** See [SYMBOLS_GUIDE.md](SYMBOLS_GUIDE.md) for a complete list of stocks, indices, ETFs, and cryptocurrencies.

## 🔒 Privacy & Security

- **100% Local**: All AI processing happens on your machine
- **No Cloud Dependencies**: No data sent to external servers
- *Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit changes (`git commit -m 'Add amazing feature'`)
4. Push to branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## License

Copyright © 2026 Your Company. All rights reserved.

## Support

- **Documentation**: [DEPLOYMENT.md](DEPLOYMENT.md)
- **Issues**: GitHub Issues
- **Email**: support@yourdomain.com

## Disclaimer

**This platform is for informational and educational purposes only. It is not financial advice. Always conduct your own research and consult with a qualified financial advisor before making investment decisions. Past performance does not guarantee future results. Trading involves risk of loss.**