DollarLiquidity.com
概要データ指標ラーニングセンターナレッジブログ
クイックアクセスTGA BalanceVIXSOFR-IORB
Policy / Reserves
Fed Balance Sheet (Total Assets)Treasury General Account (TGA)Overnight Reverse Repo (ON RRP)
Funding / Plumbing
SOFR–IORB SpreadStanding Repo Facility (SRF)
Credit / Intermediation
Bank Cash Buffer (Cash Assets / Total Assets)High Yield Spread (ICE BofA HY OAS)
Risk / Price
VIX Volatility IndexBroad Dollar Index10-Year Real Yield (TIPS)
Broader Liquidity
Net Liquidity IndexM2 Money Supply

DollarLiquidity.com

本サイトのデータは情報提供および教育目的のみで提供されています。金融アドバイスを構成するものではありません。

データソース · FRED · Treasury · NY Fed

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概要データ指標学ぶブログ

Research Framework

Methodology

Computation Pipeline

The DLI Liquidity Score synthesizes structural data from the Federal Reserve system and capital markets through a four-stage quantitative pipeline:

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1Multi-Source Ingestion

Direct integration with FRED, US Treasury Fiscal Data, and NY Fed Markets APIs — automated ingestion with cross-frequency alignment

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2Robust Statistical Normalization

Robust z-scores via 10-year rolling median and MAD (Median Absolute Deviation) — resilient to outliers and structural breaks, winsorized to [-4, +4]

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3Tiered Sub-Index Construction

The 10 scoring indicators are classified into 4 transmission tiers: Policy/Reserves, Funding/Plumbing, Credit/Intermediation, and Risk/Price, then equal-weighted within each tier.

4Composite Scoring & Adaptive Classification

Supply-side weighted 60%, price feedback 40% — regime classified via rolling 5-year percentile thresholds that adapt across macro cycles

Sub-Index Structure & Weights

The site tracks 12 indicators. The DLI score uses 10 core indicators grouped into 4 tiers. Supply-side (Policy + Funding) carries 60% total weight so the score reflects liquidity substance rather than sentiment.

追跡対象の2指標(ネット流動性とM2)は参考情報として提供されており、DLI総合スコアには含まれません。

TierWeightIndicatorTightening Signal
政策 / 準備金30%FRB 総資産↓ Falling = Tighter liquidity
TGA 残高↑ Rising = Tighter liquidity
ON RRP 残高↑ Rising = Tighter liquidity
資金調達 / 配管30%SOFR-IORB↑ Rising = Tighter liquidity
SRF 利用額↑ Rising = Tighter liquidity
信用 / 仲介20%現金バッファー↓ Falling = Tighter liquidity
HY スプレッド↑ Rising = Tighter liquidity
リスク / 価格20%VIX 指数↑ Rising = Tighter liquidity
ドル指数↑ Rising = Tighter liquidity
10Y 実質利回り↑ Rising = Tighter liquidity

DLI Liquidity Score Classification

The DLI Score uses adaptive rolling 5-year percentile thresholds to classify liquidity into four tiers, keeping signals stable and comparable across macro cycles.

PercentileLiquidity ConditionRisk Bias (Secondary)Interpretation
≤ P20AbundantRisk-seeking tiltExtremely loose liquidity — strongly favorable for risk assets
P20 – P50SupportiveMild risk-seeking tiltConditions still positive but moderating — monitor momentum shifts
P50 – P80RestrictiveMild defensive tiltConditions tightening — risk assets face moderate headwinds
≥ P80TightDefensive tiltSignificantly tight liquidity — risk assets face strong headwinds

Additional Metrics

  • 7-Day Momentum: Difference between today's DLI and 7 days ago, measuring direction and pace. Classified as Improving / Stable / Deteriorating.
  • Signal Concentration: Share of total contribution from Top 3 drivers — higher concentration means a cleaner, more interpretable signal
  • Contribution Decomposition: Daily change decomposed by indicator, showing which factors are driving DLI movement

Historical State Consistency Check (Not a Trading Backtest)

This section checks directional consistency between DLI liquidity states and subsequent asset behavior. It is not a direct return-forecasting model.

1) State First

Read liquidity state from percentile bands: supportive / neutral / tight.

2) Then Statistics

Check 20-trading-day average return and win rate under that state.

3) Validation, Not Signal

Use as model interpretability evidence, not as a standalone trading instruction.

流動性緩和≤ P20
SPX 20D Avg+2.1%SPX Win Rate68%BTC 20D Avg+5.4%BTC Win Rate63%

歴史的にリスク資産のパフォーマンスは全般的に好調ですが、ボラティリティは依然として大きい場合があります。

流動性中立P20 – P80
SPX 20D Avg+0.7%SPX Win Rate54%BTC 20D Avg+1.2%BTC Win Rate52%

方向性は弱く、他のマクロ変数の影響をより受けやすくなります。

流動性逼迫≥ P80
SPX 20D Avg-1.3%SPX Win Rate41%BTC 20D Avg-3.8%BTC Win Rate38%

歴史的にリスク資産への下押し圧力がより強く、ドローダウンの確率が高くなります。

* Sample window: 2020-2025; method: conditional 20-trading-day distributions grouped by DLI state. Historical results do not guarantee future outcomes.

Model Limitations

  • Weights are based on historical analysis and expert judgment, not ML optimization — they may not perfectly adapt to future structural market changes
  • Robust z-scores (median + MAD) substantially reduce outlier distortion compared to mean/std, but extreme tail events may still temporarily affect scores
  • The model uses daily frequency data and cannot capture intraday liquidity events (flash crashes, intraday VIX spikes)
  • Score signals have inherent lag — they are not real-time trading signals, and are better suited for strategic allocation than short-term timing

Data Sources

  • FRED — Federal Reserve Economic Data (St. Louis Fed)
  • Treasury — US Treasury Fiscal Data API
  • NY Fed — Federal Reserve Bank of New York Markets

Disclaimer

This site is for informational and educational purposes only. It does not constitute financial advice. All data comes from public sources; we do not guarantee completeness or timeliness. Investment decisions should be based on personal research and professional consultation.