# Install from PyPI pip install quantlabs # Or using uv (recommended) uv pip install quantlabs # Verify installation quantlab --version quantlab --help

# Clone the repository git clone https://github.com/nittygritty-zzy/quantlab.git cd quantlab # Using uv (recommended) uv venv source .venv/bin/activate uv sync # Or using pip python -m venv .venv source .venv/bin/activate pip install -e .

# Option A: Use external data (QuantMini on /Volumes/sandisk) # Data is already at: /Volumes/sandisk/quantmini-data/data/qlib/stocks_daily # Option B: Download community data wget https://github.com/chenditc/investment_data/releases/latest/download/qlib_bin.tar.gz mkdir -p ~/.qlib/qlib_data/cn_data tar -zxvf qlib_bin.tar.gz -C ~/.qlib/qlib_data/cn_data --strip-components=1

# Navigate to qlib examples (if using qlib_repo) cd qlib_repo/examples # Run workflow with external data uv run qrun ../../configs/lightgbm_liquid_universe.yaml

# Update the experiment ID in visualize_results.py, then: uv run python scripts/analysis/visualize_results.py

# Initialize QuantLab quantlab init # Create a tech portfolio quantlab portfolio create tech_giants --name "FAANG+ Portfolio" \ --description "Large-cap tech companies" # Add positions with target weights quantlab portfolio add tech_giants AAPL GOOGL MSFT --weight 0.20 quantlab portfolio add tech_giants META AMZN --weight 0.15 quantlab portfolio add tech_giants NVDA --weight 0.10 # View your portfolio quantlab portfolio show tech_giants # Expected output: # 📊 Portfolio: FAANG+ Portfolio # 📈 Positions: 6 # ├─ AAPL │ Weight: 20.00% │ Shares: - │ Cost Basis: - # ├─ GOOGL │ Weight: 20.00% │ Shares: - │ Cost Basis: - # ├─ MSFT │ Weight: 20.00% │ Shares: - │ Cost Basis: - # ├─ META │ Weight: 15.00% │ Shares: - │ Cost Basis: - # ├─ AMZN │ Weight: 15.00% │ Shares: - │ Cost Basis: - # └─ NVDA │ Weight: 10.00% │ Shares: - │ Cost Basis: - # Total Weight: 100.00%

# Update positions with real trade data quantlab portfolio update tech_giants AAPL \ --shares 50 \ --cost-basis 178.25 \ --notes "Bought on Q4 dip" quantlab portfolio update tech_giants GOOGL \ --shares 30 \ --cost-basis 142.50 \ --notes "Post-earnings entry" quantlab portfolio update tech_giants NVDA \ --shares 20 \ --cost-basis 485.00 \ --notes "AI boom position" # View updated portfolio quantlab portfolio show tech_giants # Expected output: # 📊 Portfolio: FAANG+ Portfolio # 📈 Positions: 6 # ├─ AAPL │ Weight: 20.00% │ Shares: 50 │ Cost: $178.25 │ "Bought on Q4 dip" # ├─ GOOGL │ Weight: 20.00% │ Shares: 30 │ Cost: $142.50 │ "Post-earnings entry" # ├─ NVDA │ Weight: 10.00% │ Shares: 20 │ Cost: $485.00 │ "AI boom position" # Total Investment: $22,812.50

# Comprehensive analysis with all data sources quantlab analyze ticker ORCL \ --include-fundamentals \ --include-options \ --include-sentiment \ --include-technicals \ --output results/orcl_analysis.json # Expected output: # 🔍 Analyzing ORCL (Oracle Corporation) # # 📈 Price Information: # Current: $145.50 # Change: +2.3% ($3.25) # Volume: 5,234,567 # # 💰 Fundamentals: # Market Cap: $401.2B # P/E Ratio: 28.5 # Forward P/E: 21.2 # Revenue Growth: 7.2% # Profit Margin: 21.5% # Debt/Equity: 2.84 # # 📊 Options Activity: # Put/Call Ratio: 0.78 (Bullish) # Implied Volatility: 22.5% # Next Earnings: 2025-03-15 (30 days) # # 📰 Sentiment Analysis: # Score: 0.72 (Positive) # Articles: 45 (7 days) # Buzz: High # # 🎯 Analyst Consensus: # Rating: Buy (12) / Hold (8) / Sell (2) # Target Price: $165.00 (+13.4%) # # ✅ Analysis complete → results/orcl_analysis.json # Visualize price action quantlab visualize price ORCL --period 90d --chart-type candlestick quantlab visualize price ORCL --period 1year --chart-type line # Quick decision check quantlab lookup get company ORCL quantlab lookup get ratings ORCL

# Analyze entire portfolio quantlab analyze portfolio tech_giants \ --include-options \ --aggregate-metrics \ --output results/tech_giants_analysis.json # Expected output: # 📊 Analyzing Portfolio: FAANG+ Portfolio (6 positions) # # Processing: [████████████████████] 6/6 # # Individual Analyses: # ✓ AAPL │ Score: 82/100 │ Sentiment: Positive │ Analysts: 85% Buy # ✓ GOOGL │ Score: 78/100 │ Sentiment: Positive │ Analysts: 80% Buy # ✓ MSFT │ Score: 88/100 │ Sentiment: Very Positive │ Analysts: 90% Buy # ✓ META │ Score: 75/100 │ Sentiment: Neutral │ Analysts: 75% Buy # ✓ AMZN │ Score: 81/100 │ Sentiment: Positive │ Analysts: 82% Buy # ⚠ NVDA │ Score: 68/100 │ Sentiment: Mixed │ Analysts: 70% Buy # # Portfolio Metrics: # Total Value: $52,450 # Avg P/E: 32.5 # Avg Sentiment: 0.68 (Positive) # Portfolio Beta: 1.15 # Weighted Analyst Rating: 80% Buy # # ⚠️ Alerts: # - NVDA showing weakness (consider reducing position) # - MSFT strongest performer (98% of analysts bullish) # Visualize portfolio performance comparison quantlab visualize compare AAPL GOOGL MSFT META AMZN NVDA \ --period 90d \ --normalize \ --output results/tech_giants_comparison.html

# Query daily stock data quantlab data query AAPL GOOGL MSFT \ --start 2024-01-01 \ --end 2025-01-15 \ --type stocks_daily \ --limit 100 # Expected output: # 📊 Querying data for 3 tickers... # # AAPL (Apple Inc.) # Date Range: 2024-01-01 to 2025-01-15 (252 trading days) # # Recent Data (last 5 days): # Date │ Open │ High │ Low │ Close │ Volume # 2025-01-15 │ $180.25 │ $182.50 │ $179.80 │ $181.75 │ 52.3M # 2025-01-14 │ $179.50 │ $181.25 │ $178.90 │ $180.25 │ 48.7M # ... # # Performance: +15.3% YTD # Volatility: 18.5% (annualized) # Visualize historical price patterns quantlab visualize price AAPL --period 2year --chart-type candlestick quantlab visualize price AAPL --interval 5min --period 5d --chart-type line # Check available data coverage quantlab data check # Expected output: # 📁 Parquet Data Availability # ✓ stocks_daily │ 13,187 tickers │ 2024-09-01 to 2025-10-15 (442 days) # ✓ stocks_minute │ 8,523 tickers │ Last 90 days # ✓ options_daily │ 3,245 tickers │ 2024-09-01 to 2025-10-15 # ✗ options_minute │ Not available

# Initialize lookup tables quantlab lookup init # Refresh data for your portfolio quantlab lookup refresh portfolio tech_giants # Expected output: # 🔄 Refreshing data for 6 tickers in tech_giants... # # Company Info: # ✓ AAPL - Apple Inc. (Technology - Consumer Electronics) # ✓ GOOGL - Alphabet Inc. (Technology - Internet Services) # ✓ MSFT - Microsoft Corporation (Technology - Software) # ✓ META - Meta Platforms Inc. (Technology - Social Media) # ✓ AMZN - Amazon.com Inc. (Consumer Cyclical - Internet Retail) # ✓ NVDA - NVIDIA Corporation (Technology - Semiconductors) # # Analyst Ratings: # ✓ AAPL - 35 analysts (Buy: 28, Hold: 6, Sell: 1) Target: $210 # ✓ GOOGL - 42 analysts (Buy: 35, Hold: 6, Sell: 1) Target: $165 # ✓ MSFT - 48 analysts (Buy: 43, Hold: 4, Sell: 1) Target: $450 # ✓ META - 38 analysts (Buy: 28, Hold: 8, Sell: 2) Target: $520 # ✓ AMZN - 45 analysts (Buy: 38, Hold: 6, Sell: 1) Target: $215 # ✓ NVDA - 40 analysts (Buy: 32, Hold: 7, Sell: 1) Target: $850 # # ✅ Refresh complete (6/6 successful) # View stored data quantlab lookup stats # Expected output: # 📊 Lookup Tables Statistics # # Company Information: 6 companies # Analyst Ratings: 6 tickers (248 total analysts) # Treasury Rates: Current (updated: 2025-10-15) # Last Updated: 2025-10-15 14:32:15

# Create portfolios for different strategies quantlab portfolio create growth --name "High Growth" \ --description "Growth stocks with P/E > 30" quantlab portfolio create value --name "Value Plays" \ --description "Undervalued stocks with P/E < 15" quantlab portfolio create dividend --name "Dividend Income" \ --description "High dividend yield stocks" # Add different stocks to each quantlab portfolio add growth NVDA TSLA SNOW --weight 0.33 quantlab portfolio add value BAC JPM WFC --weight 0.33 quantlab portfolio add dividend T VZ SO --weight 0.33 # View all portfolios quantlab portfolio list # Expected output: # 📊 Your Portfolios # # Portfolio ID │ Name │ Positions │ Total Weight │ Last Updated # ────────────────┼───────────────────┼───────────┼──────────────┼───────────── # tech_giants │ FAANG+ Portfolio │ 6 │ 100.00% │ 2025-10-15 # growth │ High Growth │ 3 │ 99.00% │ 2025-10-15 # value │ Value Plays │ 3 │ 99.00% │ 2025-10-15 # dividend │ Dividend Income │ 3 │ 99.00% │ 2025-10-15 # # Total Portfolios: 4 # Total Unique Positions: 15

# Analyze ticker specifically for options quantlab analyze ticker AAPL \ --include-options \ --no-fundamentals \ --no-sentiment \ --output results/aapl_options.json # Expected output: # 🔍 Options Analysis: AAPL # # Current Price: $181.75 # # Near-Term Expiration (30 days): # Call Options (Covered Call Candidates): # Strike │ Premium │ IV │ Delta │ Break-even │ Return # ───────┼─────────┼───────┼───────┼────────────┼──────── # $185 │ $3.85 │ 21.2% │ 0.45 │ $185.00 │ 2.1% # $190 │ $2.15 │ 19.8% │ 0.28 │ $190.00 │ 4.6% # $195 │ $0.95 │ 18.5% │ 0.15 │ $195.00 │ 7.3% # # Put Options (Cash-Secured Put Candidates): # Strike │ Premium │ IV │ Delta │ Net Cost │ Yield # ───────┼─────────┼───────┼───────┼────────────┼──────── # $175 │ $2.80 │ 22.5% │ -0.35 │ $172.20 │ 1.6% # $170 │ $1.45 │ 20.1% │ -0.20 │ $168.55 │ 0.9% # # Volatility Metrics: # Current IV: 21.2% # Historical Vol (30d): 18.5% # IV Percentile: 62% (Elevated) # # 💡 Suggestion: Good conditions for selling premium # IV elevated vs historical - consider covered calls at $190 strike # Visualize options payoff diagrams quantlab visualize options long_call --current-price 181.75 --strike 190 --premium 2.15 quantlab visualize options bull_call_spread \ --current-price 181.75 --strike1 185 --strike2 195 --premium 1.70

# Step 1: Refresh all market data quantlab lookup refresh portfolio tech_giants # Step 2: Get comprehensive analysis quantlab analyze portfolio tech_giants --aggregate-metrics # Step 3: Visualize portfolio performance quantlab visualize compare AAPL GOOGL MSFT META AMZN NVDA --period 30d --normalize # Step 4: Review individual positions quantlab visualize price AAPL --period 90d --chart-type candlestick quantlab visualize price NVDA --period 90d --chart-type candlestick # Step 5: Check for rebalancing needs quantlab portfolio show tech_giants # Step 6: Look for new opportunities quantlab data tickers --type stocks_daily | grep -E "^[A-Z]{1,4}$" | head -20 quantlab analyze ticker CRM --include-fundamentals quantlab visualize price CRM --period 90d --chart-type candlestick # Step 7: Update positions based on analysis quantlab portfolio update tech_giants NVDA --weight 0.05 --notes "Reduced - valuation concerns" quantlab portfolio add tech_giants CRM --weight 0.05 --notes "New position - cloud growth" # Step 8: Export for records quantlab analyze portfolio tech_giants --output results/monthly_review_2025_10.json

# Create a monitoring script cat > scripts/daily_monitor.sh << 'EOF' #!/bin/bash DATE=$(date +%Y-%m-%d)  echo "🔍 Daily Portfolio Monitor - $DATE" echo "=================================="  # Analyze each portfolio for portfolio in tech_giants growth value dividend; do  echo ""  echo "📊 Portfolio: $portfolio"  quantlab analyze portfolio $portfolio \  --include-options \  --output "results/monitoring/${portfolio}_${DATE}.json" 2>&1 | \  grep -E "(Score:|Sentiment:|Analysts:|⚠|❌)" done  # Check treasury rates for risk-free rate echo "" echo "📈 Current Treasury Rates:" quantlab lookup get treasury 10y  echo "" echo "✅ Monitoring complete" EOF chmod +x scripts/daily_monitor.sh # Run daily monitoring ./scripts/daily_monitor.sh # Expected output: # 🔍 Daily Portfolio Monitor - 2025-10-15 # ================================== # # 📊 Portfolio: tech_giants # ✓ AAPL │ Score: 82/100 │ Sentiment: Positive # ✓ GOOGL │ Score: 78/100 │ Sentiment: Positive # ⚠ NVDA │ Score: 68/100 │ Sentiment: Mixed # # 📈 Current Treasury Rates: # 10-Year Treasury: 4.25% (as of 2025-10-15) # # ✅ Monitoring complete

# Candlestick charts (daily data) quantlab visualize price AAPL --period 90d --chart-type candlestick # Line charts with volume quantlab visualize price AAPL --period 1year --chart-type line # Intraday charts (5min, 15min, 1hour intervals) quantlab visualize price AAPL --interval 5min --period 5d --chart-type candlestick quantlab visualize price NVDA --interval 1hour --period 30d --chart-type line

# Compare normalized performance quantlab visualize compare AAPL GOOGL MSFT --period 90d --normalize # Absolute price comparison quantlab visualize compare AAPL GOOGL MSFT --period 1year

# Single leg strategies quantlab visualize options long_call --current-price 180 --strike 190 --premium 2.15 quantlab visualize options long_put --current-price 180 --strike 175 --premium 2.80 # Spread strategies quantlab visualize options bull_call_spread \ --current-price 180 --strike1 185 --strike2 195 --premium 1.70 quantlab visualize options iron_condor \ --current-price 180 --strike1 170 --strike2 175 --strike3 195 --strike4 200

# Visualize backtest performance quantlab visualize backtest results/mlruns/[experiment_id]

# Test Alpha158 features python scripts/tests/test_qlib_alpha158.py # Test data conversion python scripts/data/convert_to_qlib.py # Refresh latest data python scripts/data/refresh_today_data.py