StationFX Real Federal Funds Rate is a paid API for AI agents from stationfx.com, paid per call via x402, $0.008/call, status unknown (last checked 2026-10-02).
Returns the pre-computed daily real federal funds rate (fed funds effective rate minus CPI YoY inflation), signaling whether U.S. monetary policy is restrictive or accommodative in real terms.
Federal funds effective rate minus CPI YoY inflation. Measures whether monetary policy is restrictive or accommodative in real terms. Negative real rates = loose policy (historically supports risk assets). Positive real rates = restrictive policy (historically pressures valuations). Pre-computed daily.
Returns a time-series array of daily real federal funds rate observations, each including the raw value (fed funds rate minus CPI YoY), month-over-month and year-over-year changes and percent changes, 12-month and 5-year Z-scores, 5-year percentile rank, 3-month and 12-month rolling averages, and an above-trend flag. Supports JSON or compact toon format.
GEThttps://stationfx.com/economic-data/cross-signal/real-federal-funds-rate?utm_source=zero.xyzUse this endpoint when you need a pre-computed, daily-updated real federal funds rate signal without having to fetch and subtract CPI and fed funds data yourself. It is ideal for macroeconomic regime detection, risk asset allocation models, or policy stance monitoring. Prefer this over raw FRED data endpoints when you want enriched statistics (Z-scores, percentile ranks, rolling averages, trend flags) already attached to each data point.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"schema": {
"type": "object",
"properties": {
"data": {
"type": "array",
"items": {
"type": "object",
"properties": {
"date": {
"type": "string",
"description": "Observation date YYYY-MM-DD"
},
"value": {
"type": "number",
"description": "Raw observed value in series units"
},
"mom_pct": {
"type": "number",
"description": "Month-over-month % change"
},
"yoy_pct": {
"type": "number",
"description": "Year-over-year % change"
},
"zscore_5y": {
"type": "number",
"description": "Z-score relative to trailing 5 years"
},
"mom_change": {
"type": "number",
"description": "Month-over-month absolute change"
},
"yoy_change": {
"type": "number",
"description": "Year-over-year absolute change"
},
"zscore_12m": {
"type": "number",
"description": "Z-score relative to trailing 12 months"
},
"above_trend": {
"type": "integer",
"description": "1 if value is above long-run trend, else 0"
},
"pct_rank_5y": {
"type": "number",
"description": "Percentile rank over trailing 5 years (0-100)"
},
"rolling_3m_avg": {
"type": "number",
"description": "3-month rolling average"
},
"rolling_12m_avg": {
"type": "number",
"description": "12-month rolling average"
},
"trend_direction": {
"type": "integer",
"description": "Trend: 1 rising, -1 falling, 0 flat"
}
}
},
"description": "Observations ordered by date ascending"
},
"meta": {
"type": "object",
"description": "Series metadata: source_key (FRED series ID), units, frequency (D/W/M/Q/A), date_from, date_to, fields"
}
},
"description": "Station f(x) response with metadata and pre-computed derived metrics"
},
"example": {
"data": [
{
"date": "2024-01-01",
"value": 5.33,
"mom_pct": 0,
"yoy_change": 0.5,
"zscore_12m": 1.2,
"trend_direction": 1
}
],
"meta": {
"frequency": "M",
"source_key": "SERIES_ID"
}
}
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