US bank lending standards signals (SLOOS tightening, credit conditions)
Quarterly US credit-conditions signals derived from FRED's Senior Loan Officer Opinion Survey (SLOOS): net percentages of banks tightening lending standards for C&I loans, with quarter-on-quarter and year-on-year changes in percentage points, 30-quarter annualized change volatility, 1-quarter momentum, 3-sigma anomaly flags vs a trailing 12-quarter baseline, naive-drift 1-quarter forecasts, a per-quarter cross-series volatility rank, tightening regime flags with 4-year z-scores, and the large-firm minus small-firm tightening spread (the flight-to-quality gauge). 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); underlying survey: Board of Governors of the Federal Reserve System.
Qualité
Attribution
Federal Reserve Bank of St. Louis (FRED; underlying survey: Board of Governors of the Federal Reserve System; derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Observation date (FRED API field date; YYYY-MM-DD, first day of the reference quarter). |
| country | string | |
| country_code | string | |
| series_id | string | FRED series ID, e.g. DRTSCILM, DRTSCIS; resolves to the series page at https://fred.stlouisfed.org/series/<id>. |
| series_label | string | Official FRED series title as published for the series (Senior Loan Officer Opinion Survey on Bank Lending Practices, Board of Governors of the Federal Reserve System). |
| value | float | Observation value as published by FRED for this series: net percentage of domestic banks tightening standards for commercial and industrial loans (positive = tightening on net, negative = easing on net); see the series notes for methodology and revisions. |
| change_qoq | float | |
| change_yoy | float | |
| volatility_30d | float | |
| momentum_3m | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| tightening_flag | integer | |
| tightening_z_4y | float | |
| large_small_spread | float |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | change_qoq | change_yoy | volatility_30d | momentum_3m | anomaly_flag | forecast_1m | rank | tightening_flag | tightening_z_4y | large_small_spread |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1990-04-01 | United States | USA | DRTSCILM | Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms | 54.4 | — | — | — | — | 0 | — | — | 1 | — | 1.6999999999999957 |
| 1990-04-01 | United States | USA | DRTSCIS | Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Small Firms | 52.7 | — | — | — | — | 0 | — | — | 1 | — | 1.6999999999999957 |
| 1990-07-01 | United States | USA | DRTSCILM | Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms | 46.7 | -7.699999999999996 | — | — | -7.699999999999996 | 0 | — | — | 1 | — | 12.800000000000004 |
| 1990-07-01 | United States | USA | DRTSCIS | Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Small Firms | 33.9 | -18.800000000000004 | — | — | -18.800000000000004 | 0 | — | — | 1 | — | 12.800000000000004 |
| 1990-10-01 | United States | USA | DRTSCILM | Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms | 54.2 | 7.5 | — | — | 7.5 | 0 | — | — | 1 | — | 13.5 |
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/sloos_signals/us_bank_lending_standards_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/sloos_signals/us_bank_lending_standards_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/sloos_signals/us_bank_lending_standards_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.