Interactive Dashboard¶

The Interactive Dashboard provides a live web interface for viewing and updating your investment analysis. It compares multiple valuation models side-by-side with real-time data updates.

Quick Start¶

# Start the dashboard server
poetry run python scripts/dashboard_server.py

# Dashboard opens automatically at http://localhost:8080
# Click "Update Data" button to refresh valuations

Features¶

Live Valuation Comparison¶

Traditional DCF: Standard discounted cash flow analysis
Enhanced DCF: Dividend-aware DCF accounting for capital allocation efficiency
Simple Ratios: Benjamin Graham-style ratio-based valuation

Interactive Updates¶

One-Click Refresh: Update all valuations with button click
Real-Time Prices: Current market data with live calculations
Background Processing: Updates run without blocking the interface
Visual Feedback: Button shows progress (⏳ Updating... → ✅ Updated!)

User-Friendly Interface¶

Tooltips: Hover over column headers for detailed metric explanations
Professional Styling: Clean, responsive design with hover effects
Auto-Refresh: Page refreshes automatically during updates
Error Handling: Graceful fallbacks for failed calculations

Dashboard Layout¶

Header Section¶

Last Updated: Timestamp of most recent data refresh
Stocks Analyzed: Total number of stocks in current analysis
Update Controls: Command line reference and update button

Valuation Table¶

Each row shows a stock with columns for:

Column	Description
Ticker	Stock symbol
Current Price	Latest market price per share
Fair Value	Estimated intrinsic value from each model
Upside/Downside	Percentage difference between fair value and current price

Model Comparison¶

Green percentages: Stock is undervalued (potential upside)
Red percentages: Stock is overvalued (potential downside)
Missing data: Shows "-" for unavailable calculations

Hover over any column header to see detailed explanations:

Traditional DCF: Projects future cash flows and discounts to present value
Enhanced DCF: Accounts for dividend policy and reinvestment efficiency
Simple Ratios: Uses P/E, P/B, P/S ratios with sector adjustments
Upside/Downside: Shows margin of safety for investment decisions

Technical Details¶

Server Architecture¶

HTTP Server: Python built-in server for local access
Background Processing: Valuations run in separate threads
Auto-Discovery: Browser opens automatically on startup
Port: Runs on localhost:8080 by default

Data Updates¶

Button Click: User clicks "Update Data"
API Request: Frontend sends POST to /update endpoint
Background Task: Server runs valuation calculations in thread
Immediate Response: User sees progress feedback
Auto-Reload: Page refreshes with updated data

Error Handling¶

Timeout Protection: Individual stock calculations timeout after 30 seconds
Graceful Failures: Failed calculations show "-" instead of errors
Connection Issues: Falls back to command line instructions
Data Validation: Handles missing or invalid financial data

Customization¶

Default Stock List¶

The dashboard analyzes these stocks by default: - Growth: AAPL, MSFT, GOOGL, AMZN, TSLA, NVDA - Dividend: JNJ, PG, KO
- Mixed: JPM, HD

Modifying Stock List¶

Edit scripts/dashboard_server.py and update the tickers list:

# Default tickers
tickers = ['AAPL', 'MSFT', 'GOOGL', 'AMZN', 'JNJ', 'PG', 'KO', 'JPM', 'HD', 'TSLA', 'NVDA']

Performance Settings¶

Timeout per stock: 30 seconds (configurable)
Max workers: 3 concurrent threads
Update frequency: Manual button clicks only

Troubleshooting¶

Common Issues¶

Port Already in Use

# Kill existing server
lsof -ti:8080 | xargs kill -9

Browser Doesn't Open - Manually visit http://localhost:8080 - Check firewall settings - Try different browser

Update Button Not Working - Check server logs in terminal - Ensure network connection for financial data - Try refreshing page manually

Missing Data - Some stocks may lack required financial data - Enhanced DCF requires FCF, shares, and current price - Simple Ratios needs P/E, P/B, P/S ratios

Performance Tips¶

Close other applications using network bandwidth during updates
Use wired connection for faster financial data downloads
Update during market hours for most current prices
Limit concurrent updates to avoid API rate limits

Integration with Analysis Pipeline¶

The dashboard uses the same analysis pipeline as the command-line tools:

DCF Model: src/invest/dcf.py
Enhanced DCF: src/invest/dcf_enhanced.py
Simple Ratios: src/invest/simple_ratios.py
Data Provider: Yahoo Finance via src/invest/data/yahoo.py

This ensures consistency between dashboard results and systematic analysis reports.