Portfolio Tracker - Quantitative Analytics Engine

A portfolio management and risk analytics system

🎯 Overview

A comprehensive portfolio analytics engine with interactive dashboard for tracking investments, analyzing performance, and managing risk.

Key Features

• 📊 Dashboard - Portfolio analytics visualization with Streamlit
• 💹 Performance Tracking - Returns, drawdowns, and benchmark comparisons
• ⚠️ Risk Analytics - VaR, Sharpe ratios, and comprehensive risk metrics
• 🔄 Multiple Accounting Methods - FIFO, LIFO, and Average Cost
• 🖼️ Visualizations - Performance charts and benchmark comparisons
• 🗃️ Data Management - SQLAlchemy ORM with sample data generation

Core Components

• Data Ingestion: API fetchers and CSV loaders
• Analytics Engine: Portfolio performance and risk calculations
• Data Layer: SQLAlchemy ORM with normalized schema
• Dashboard: Interactive Streamlit web interface

🚀 Quick Start

1. Setup Environment

# Clone and install
git clone https://github.com/jarn/tracker-demo.git
cd tracker-demo

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

# Install dependencies
pip install -e .

2. Generate Sample Data

# Create sample portfolio data
python scripts/generate_sample_data.py

# Initialize database and load data
python scripts/migrate.py init --direct
python scripts/loader.py all

📊 Analytics Data Showcase

Run Analytics Script

python scripts/show_analytics.py

Portfolio Performance Example

============================================================
📊 PORTFOLIO TRACKER ANALYTICS RESULTS
============================================================

📋 Data Overview
------------------------------
   Transactions:     6 records
   Market Data:      365 price points
   Cash Flows:       18 entries
   Market Data Columns: ['AAPL', 'BTC-USD', 'QQQ', 'SPY', 'CASH']
   Period:           2024-01-01 to 2024-12-30
   Duration:         364 days

💰 Portfolio Performance
------------------------------
   Current Value:    $34,657.24
   Total Return:     37.92%
   Annualized:       37.95%
   Volatility:       16.13%
   Sharpe Ratio:     2.352

⚠️ Risk Metrics
------------------------------
   Max Drawdown:     -10.98%
   Drawdown Days:    90 days
   VaR (95%):        $454.75
   CVaR (95%):       $703.28
   Downside Dev:     10.62%
   Sortino Ratio:    2.963
   Calmar Ratio:     3.457

🥧 Current Allocation
------------------------------
   SPY         :    36.33%
   AAPL        :    28.36%
   QQQ         :    18.57%
   BTC-USD     :     16.5%

📈 Benchmark Analysis
------------------------------
   Portfolio Return: 37.95%
   Benchmark (ACWI): 20.28%
   Alpha:            11.73%
   Beta:             1.139
   Outperformance:   17.67%

Launch Dashboard

# Start interactive dashboard
streamlit run dashboard.py --server.port 8506

Open http://localhost:8506 to view your portfolio analytics dashboard!

Dashboard Features

• Performance Charts: Portfolio value over time with markers
• Risk Analysis: Comprehensive risk metrics
• Allocation View: Current portfolio allocation pie charts
• Position Details: Holdings with P&L breakdown
• Benchmark Comparison: Performance vs market indices

🛠️ Project Structure

tracker/
├── src/tracker/           # Main package
│   ├── analytics/         # Performance and risk analysis
│   │   ├── accounting/    # Accounting methods for cost analysis
│   │   └── core/          # Core analytics modules (Performance, Risk)
│   ├── api/               # REST API
│   ├── config/            # Configuration management
│   ├── data/              # Data management and models
│   │   ├── access/        # External data sources
│   │   ├── managers/      # Data managers (CSV, DB)
│   │   ├── orm/           # SQLAlchemy ORM models
│   │   └── repos/         # Models repositories
│   └── services/          # Business logic and services
├── scripts/               # Entry point scripts
├── sql/                   # Database schema and queries
├── alembic/               # Database model versioning
├── data/                  # Data files
├── notebooks/             # Dashboards examples
├── examples/              # Usage & Dev examples
├── docs/                  # Documentation
├── logs/                  # Application logs
├── dl/                    # Data loading files
└── tests/                 # Unit and integration tests

License

MIT License - see LICENSE file for details.