macro-regime-detector

Cross-asset ratio analysis identifies structural macro regime transitions by evaluating metrics like RSP/SPY concentration, yield curves, and credit conditions to classify shifts between broadening, contraction, and inflationary states.

You need access to financial data APIs to retrieve market metrics, alongside Python libraries like pandas and numpy to process the datasets for regime classification and reporting.

Yes, you can use Python and matplotlib to generate comprehensive reports and visualizations that map structural transitions between Concentration, Broadening, Contraction, Inflationary, and Transitional macro regimes.

You classify market states by analyzing equity-bond relationships, sector rotation, and size factors to categorize the current environment into specific regimes like Broadening or Contraction for risk management.

Apply cross-asset ratio analysis when you need to identify long-term structural macro regime transitions for strategic portfolio positioning, rather than relying on standard market analysis for short-term trading signals.