Methodology

Indicator Universe

12 indicators across 4 scoring tiers plus a context tier. Each indicator's direction is normalized so a positive z-score always means "tighter" liquidity.

Context (not scored)

• Net Liquidity = Fed BS − TGA − ON RRP
• M2 Money Supply

Scoring

1. Robust z-score

For each indicator, we compute a robust z-score using the median and median absolute deviation (MAD) over a rolling 10-year window:

z = (value − median) / (MAD × 1.4826)

The 1.4826 constant makes MAD comparable to standard deviation for normally distributed data. Z-scores are winsorized to [−4, +4] to prevent extreme observations from dominating the composite. We use median/MAD rather than mean/std for resilience to structural breaks (regime changes, COVID, etc.).

2. Direction normalization

Some indicators rise when liquidity tightens (TGA, ON RRP, VIX, HY Spread, …); others fall (Fed BS, Bank Cash Buffer). For "falling-is-tightening" indicators we negate the raw z-score so a positive z always means "tighter" across every indicator.

3. Composite

composite = Σ (z_i × weight_i)

  Tier A (Policy/Reserves):       3 × 0.10 = 0.30
  Tier B (Funding/Plumbing):      2 × 0.15 = 0.30
  Tier C (Credit/Intermediation): 2 × 0.10 = 0.20
  Tier D (Risk/Price):            3 × (1/15) ≈ 0.20
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When indicators are missing on a given day, the remaining weights are renormalized so a partial-data day still produces a comparable composite.

4. Regime classification

We rank today's composite within the rolling 5-year history of composites and assign a regime:

• ● Loose — ≤ P20
• ● Mildly Loose — P20–P50
• ● Mildly Tight — P50–P80
• ● Tight — ≥ P80

5. Momentum & concentration

• Momentum: composite_today − composite_7d_ago. >+0.15 = deteriorating, <−0.15 = improving, else stable.
• Concentration: top-3 |contributions| / total |contributions|. High concentration = signal driven by a few drivers.

Asset Impact Lens

For SPX, QQQ, and BTC we precompute three relationship windows on every cron cycle (gold temporarily dropped — FRED retired the LBMA daily series; replacement TBD):

• Rolling correlations (30D / 90D / 180D) between the daily DLI composite and daily log returns.
• Lead–lag correlations (DLI leads asset returns by 10D / 20D / 60D).
• Conditional state outcomes: average forward 20-day cumulative log return + win-rate when DLI was in the loose (≤P20) or tight (≥P80) state.

Data Sources

• FRED — Federal Reserve Bank of St. Louis, public economic time series
• US Treasury Fiscal Data — Daily Treasury Statement (TGA balance)
• NY Fed Markets — Standing Repo Facility usage