macro-regime-detector

To detect macro regime shifts, analyze cross-asset ratios like RSP/SPY and 10Y-2Y yield spread to classify structural transitions into Concentration, Broadening, Contraction, Inflationary, or Transitional regimes for long-horizon positioning.

Cross-asset signals used to classify market regimes include RSP/SPY, 10Y-2Y yield spread, HYG/LQD, IWM/SPY, SPY/TLT, and XLY/XLP ratios, which compute composite scores to identify structural transitions and assess portfolio posture.

Yes, you need a Financial Modeling Prep API key to fetch the approximately 600 days of daily time-series data required to compute cross-asset component scores and generate a macro regime transition report.

Generate a report with transition probabilities by running the detector to compute six cross-asset component scores, which outputs a detailed JSON and Markdown file with regime evidence, confidence assessment, and suggested portfolio posture.

Cross-asset regime detection handles missing data gracefully by computing available component scores and providing confidence assessments, ensuring the workflow still outputs a structured regime classification and transition probability metrics.

Monthly signals for regime detection limit the analysis to structural macro transitions rather than high-frequency trading, requiring about 600 days of daily data to smooth noise and accurately classify long-horizon portfolio postures.