Macro Regime Detector

Detect structural macro regime transitions using monthly-frequency cross-asset ratio analysis. This skill identifies 1-2 year regime shifts that inform strategic portfolio positioning.

When to Use

• User asks about current macro regime or regime transitions
• User wants to understand structural market rotations (concentration vs broadening)
• User asks about long-term positioning based on yield curve, credit, or cross-asset signals
• User references RSP/SPY ratio, IWM/SPY, HYG/LQD, or other cross-asset ratios
• User wants to assess whether a regime change is underway

Workflow

1. Load reference documents for methodology context:

   • references/regime_detection_methodology.md
   • references/indicator_interpretation_guide.md

2. Execute the main analysis script:

   python3 -m pip install -r skills/macro-regime-detector/requirements.txt
   uv run python3 skills/macro-regime-detector/scripts/macro_regime_detector.py --output-dir reports/
   

   This fetches 600 days of data for 9 ETFs. With an FMP key, the client tries FMP first and fetches Treasury rates (~10 API calls total), then falls back to yfinance for unavailable ETF history. Without an FMP key, it runs in yfinance-only mode and uses SHY/TLT as the yield-curve fallback.

   The detector fails closed and writes no report when none of its six components has usable data. Do not treat a missing report or non-zero exit as a valid low-transition regime.

3. Read the generated Markdown report and present findings to user.

4. Provide additional context using references/historical_regimes.md when user asks about historical parallels.

Prerequisites

• Python dependencies (required): install requirements.txt, including yfinance and requests
• FMP API Key (optional): set FMP_API_KEY or pass --api-key to use FMP and Treasury data before the yfinance/SHY-TLT fallbacks
• The FMP free tier may not serve every ETF; unavailable symbols automatically use yfinance

6 Components

5 Regime Classifications

• Concentration: Mega-cap leadership, narrow market
• Broadening: Expanding participation, small-cap/value rotation
• Contraction: Credit tightening, defensive rotation, risk-off
• Inflationary: Positive stock-bond correlation, traditional hedging fails
• Transitional: Multiple signals but unclear pattern

Output

• macro_regime_YYYY-MM-DD_HHMMSS.json — Structured data for programmatic use
• macro_regime_YYYY-MM-DD_HHMMSS.md — Human-readable report with:
  1. Current Regime Assessment
  2. Transition Signal Dashboard
  3. Component Details
  4. Regime Classification Evidence
  5. Portfolio Posture Recommendations

Relationship to Other Skills

Script Arguments

python3 macro_regime_detector.py [options]

Options:
  --api-key KEY       FMP API key (default: $FMP_API_KEY)
  --output-dir DIR    Output directory (default: current directory)
  --days N            Days of history to fetch (default: 600)

Resources

• references/regime_detection_methodology.md — Detection methodology and signal interpretation
• references/indicator_interpretation_guide.md — Guide for interpreting cross-asset ratios
• references/historical_regimes.md — Historical regime examples for context