US household balance signals (savings buffer, debt-service strain, savings/dsr anomalies)
Monthly/quarterly signals derived from BEA and Federal Reserve household-finances data (redistributed by FRED): 30-period annualized change volatility, ~3-month momentum, year-over-year change in percentage points, 3-sigma anomaly flags vs a trailing 12-month baseline, naive-drift 1-month forecasts, a per-date cross-series volatility rank, and the household savings buffer (saving rate minus debt service ratio — the net cash-buffer gauge). Covers the personal saving rate and the household debt service ratio. 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 data: U.S. Bureau of Economic Analysis and Board of Governors of the Federal Reserve System.
Quality
Attribution
Federal Reserve Bank of St. Louis (FRED; underlying data: U.S. Bureau of Economic Analysis and Board of Governors of the Federal Reserve System; derived signals by Frontier Data Hub)
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Observation date (FRED API field date; YYYY-MM-DD). |
| country | string | |
| country_code | string | |
| series_id | string | FRED series ID (PSAVERT, TDSP); FRED IDs resolve to the series page at https://fred.stlouisfed.org/series/<id>. |
| series_label | string | Official FRED series title as published for the series (U.S. Bureau of Economic Analysis and Board of Governors of the Federal Reserve System data). |
| value | float | Observation value as published by FRED: personal saving rate as a percent of disposable personal income (PSAVERT); household debt service payments as a percent of disposable personal income (TDSP). See the series notes for methodology. |
| volatility_30d | float | |
| momentum_3m | float | |
| yoy_change | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| savings_buffer | float |
Sample rows
| date | country | country_code | series_id | series_label | value | volatility_30d | momentum_3m | yoy_change | anomaly_flag | forecast_1m | rank | savings_buffer |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1959-01-01 | United States | USA | PSAVERT | Personal Saving Rate | 11.3 | — | — | — | 0 | — | — | — |
| 1959-02-01 | United States | USA | PSAVERT | Personal Saving Rate | 10.6 | — | — | — | 0 | — | — | — |
| 1959-03-01 | United States | USA | PSAVERT | Personal Saving Rate | 10.3 | — | — | — | 0 | — | — | — |
| 1959-04-01 | United States | USA | PSAVERT | Personal Saving Rate | 11.2 | — | -0.10000000000000142 | — | 0 | — | — | — |
| 1959-05-01 | United States | USA | PSAVERT | Personal Saving Rate | 10.6 | — | 0 | — | 0 | — | — | — |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/household_balance_signals/us_household_balance_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/household_balance_signals/us_household_balance_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)API endpoint: https://datazimuts.com/v1/datasets/household_balance_signals/us_household_balance_signals
Tip: fetch /llms.txt for the full machine-readable catalog.