Metric Methodology &
Calculation Framework
Every derived metric on this platform is documented with its precise formula, underlying data components, economic intuition, and real-world institutional use cases. All Z-scores use a 25-year rolling window to capture full debt and monetary cycles post-1971.
Core Analytical Principles
Regime-Invariant Design
All metrics are normalised against long-run distributions, not recent history. This prevents cycle bias and ensures signals remain comparable across monetary regimes.
Institutional Source Hierarchy
Primary sources (FRED, IMF, BIS, RBI DBIE) take precedence over secondary aggregators. Market data (Yahoo Finance) is used only for high-frequency price signals.
Transparent Composition
Every composite metric documents its weights and component definitions. There are no black-box signals — every formula is reproducible by any analyst with access to the same inputs.
Metric Definitions
Macro Regime Classification
The platform classifies the macro environment into three regimes using a deterministic rules-based model combining normalised liquidity and volatility signals. No machine learning or probabilistic inference is used — the classification is fully transparent and auditable.
Tightening Risk
Net Liquidity Z < −1.5 OR SOFR Spread > 15bpsCentral bank liquidity withdrawal is at a pace that historically precedes credit event risk. Reduce duration; increase defensive positioning.
Liquidity Expansion
Net Liquidity Z > 1.5 AND SOFR Spread < 5bpsAggressive central bank accommodation or TGA drain is injecting reserves into the system. Risk appetite historically elevated in this regime.
Neutral / Structural
−1.5 ≤ Net Liquidity Z ≤ 1.5Signals within ±1.5σ of the 25-year mean. Market is in a trend-following structural phase. Factor and momentum strategies historically outperform.