US monetary policy signals (money-supply growth, policy-rate momentum, QE/QT tracker)
Daily-to-monthly monetary signals derived from FRED's US money and policy series: 30-period annualized change volatility, 3-month momentum, year-over-year change (the money-supply growth gauge), 3-sigma anomaly flags, naive-drift 1-month forecasts, a per-date cross-series volatility rank, and the QE/QT tracker (3-month percent change of total Federal Reserve balance-sheet assets; negative = quantitative tightening). Covers the effective federal funds rate (daily and monthly), M1, M2, the monetary base and total Fed balance-sheet assets. All rows are normalized to country_code USA so they join cleanly with US macro data. Raw series: Federal Reserve Bank of St. Louis (FRED; US-government series from the Board of Governors of the Federal Reserve System).
Qualité
Attribution
Federal Reserve Bank of St. Louis (FRED; derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Observation date (FRED API field date; YYYY-MM-DD). |
| country | string | |
| country_code | string | |
| series_id | string | FRED series ID, e.g. DFF, FEDFUNDS, M2SL, M1SL, BOGMBASE, WALCL; resolves to the series page at https://fred.stlouisfed.org/series/<id>. |
| series_label | string | Official FRED series title as published for the series. |
| value | float | Observation value as published by FRED for this series (federal funds rate in percent; M1, M2 and monetary base in billions of dollars; total Fed balance-sheet assets WALCL in millions of dollars); see the series notes for methodology and revisions. |
| volatility_30d | float | |
| momentum_3m | float | |
| yoy_change_pct | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| qt_qe_momentum | float |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | volatility_30d | momentum_3m | yoy_change_pct | anomaly_flag | forecast_1m | rank | qt_qe_momentum |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1954-07-01 | United States | USA | DFF | Federal Funds Effective Rate | 1.13 | — | — | — | 0 | — | — | — |
| 1954-07-01 | United States | USA | FEDFUNDS | Federal Funds Effective Rate | 0.8 | — | — | — | 0 | — | — | — |
| 1954-07-02 | United States | USA | DFF | Federal Funds Effective Rate | 1.25 | — | — | — | 0 | — | — | — |
| 1954-07-03 | United States | USA | DFF | Federal Funds Effective Rate | 1.25 | — | — | — | 0 | — | — | — |
| 1954-07-04 | United States | USA | DFF | Federal Funds Effective Rate | 1.25 | — | — | — | 0 | — | — | — |
Télécharger un échantillon
Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).
Utiliser avec un LLM
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/monetary_signals/us_monetary_policy_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/monetary_signals/us_monetary_policy_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API: https://datazimuts.com/v1/datasets/monetary_signals/us_monetary_policy_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.