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Quick Start Guide

On Your Local Machine

Step 1: Clone the Project

cd ~/projects  # or wherever you keep code
git clone <your-repo-url> capital-markets-intelligence
cd capital-markets-intelligence

Step 2: Set Up Python Environment

# Create virtual environment
python3 -m venv venv

# Activate it
source venv/bin/activate  # On Mac/Linux
# OR
venv\Scripts\activate     # On Windows

# Install dependencies
pip install -r requirements.txt

Step 3: Run Week 1 Scripts

# Fetch IPO data
python scripts/01_fetch_ipo_data.py

# Fetch M&A data
python scripts/02_fetch_mna_data.py

# Check your data
ls -la data/raw/

Step 4: Use Claude Code for Development

When you want Claude to help you build or debug:

# Start Claude Code in this folder
claude-code

# Then ask Claude:
# "Help me debug the IPO fetch script"
# "Add error handling to the M&A script"
# "Build a stress testing module"

Step 5: Commit Your Work to Git

# After each successful script run
git add scripts/01_fetch_ipo_data.py
git commit -m "Add IPO data scraper with SEC EDGAR + Renaissance Capital integration"

git add data/raw/ipo_data_raw.csv
git commit -m "Add sample IPO dataset (50 records)"

# Push to GitHub
git push origin main

Week 1 Checklist

  • Clone repo locally
  • Set up Python venv
  • Run pip install -r requirements.txt
  • Execute scripts/01_fetch_ipo_data.py
  • Verify data/raw/ipo_data_raw.csv exists
  • Execute scripts/02_fetch_mna_data.py
  • Verify data/raw/mna_data_raw.csv exists
  • Run git add + git commit for each major milestone
  • Push to GitHub

Week 2: Analysis

Once data is gathered:

# Start Jupyter
jupyter notebook

# Open: analysis/market_sentiment.ipynb
# Follow the template to:
# 1. Load IPO + M&A data
# 2. Plot trends
# 3. Calculate metrics
# 4. Generate visualizations

Week 3-4: Stress Testing & Memos

# Run stress test model
python scripts/03_stress_test_model.py

# Generate case studies
python scripts/04_case_study_builder.py

# Export outputs
ls -la output/

Troubleshooting

"ModuleNotFoundError: No module named 'pandas'"

pip install pandas
# OR re-run: pip install -r requirements.txt

"SEC EDGAR API timeout"

The SEC API sometimes has rate limits. The scripts have built-in delays. If it times out, just run it again in 5 minutes.

"No data in data/raw/"

Make sure you ran the scripts successfully. Check:

python scripts/01_fetch_ipo_data.py  # Should print ✓ checkmarks

Getting Help

  1. Claude Code: Run claude-code in the project folder
  2. Debug a script: claude-code + "Debug this error: [error message]"
  3. Add a feature: claude-code + "Add X to the Y script"

Next Steps

  1. Run Week 1 scripts (this week)
  2. Build Week 2 analysis notebooks (next week)
  3. Week 3-4: Stress testing + case studies
  4. Week 5: Export → Opus for memo writing

Good luck! 🚀
⚡