Detect structural macro regime transitions (1-2 year horizon) using cross-asset ratio analysis. Analyze RSP/SPY concentration, yield curve, credit conditions, size factor, equity-bond relationship, and sector rotation to identify regime shifts between Concentration, Broadening, Contraction, Inflationary, and Transitional states. Run when user asks about macro regime, market regime change, structural rotation, or long-term market positioning.
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.
Load reference documents for methodology context:
references/regime_detection_methodology.mdreferences/indicator_interpretation_guide.mdExecute the main analysis script:
python3 skills/macro-regime-detector/scripts/macro_regime_detector.py
This fetches 600 days of data for 9 ETFs + Treasury rates (10 API calls total).
Read the generated Markdown report and present findings to user.
Provide additional context using references/historical_regimes.md when user asks about historical parallels.
FMP_API_KEY environment variable or pass --api-key| # | Component | Ratio/Data | Weight | What It Detects |
|---|---|---|---|---|
| 1 | Market Concentration | RSP/SPY | 25% | Mega-cap concentration vs market broadening |
| 2 | Yield Curve | 10Y-2Y spread | 20% | Interest rate cycle transitions |
| 3 | Credit Conditions | HYG/LQD | 15% | Credit cycle risk appetite |
| 4 | Size Factor | IWM/SPY | 15% | Small vs large cap rotation |
| 5 | Equity-Bond | SPY/TLT + correlation | 15% | Stock-bond relationship regime |
| 6 | Sector Rotation | XLY/XLP | 10% | Cyclical vs defensive appetite |
macro_regime_YYYY-MM-DD_HHMMSS.json — Structured data for programmatic usemacro_regime_YYYY-MM-DD_HHMMSS.md — Human-readable report with:
| Aspect | Macro Regime Detector | Market Top Detector | Market Breadth Analyzer |
|---|---|---|---|
| Time Horizon | 1-2 years (structural) | 2-8 weeks (tactical) | Current snapshot |
| Data Granularity | Monthly (6M/12M SMA) | Daily (25 business days) | Daily CSV |
| Detection Target | Regime transitions | 10-20% corrections | Breadth health score |
| API Calls | ~10 | ~33 | 0 (Free CSV) |
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)
references/regime_detection_methodology.md — Detection methodology and signal interpretationreferences/indicator_interpretation_guide.md — Guide for interpreting cross-asset ratiosreferences/historical_regimes.md — Historical regime examples for context