StationFX Velocity of M2 Money Stock

x402

StationFX Velocity of M2 Money Stock is a paid API for AI agents from stationfx.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-01).

Returns quarterly time-series data for M2 money velocity (GDP/M2), with trend, z-score, and momentum statistics for monetary policy analysis.

Price / call$0.005

Seller volume →—

Success—

StatusUnknown

How this service works

GDP divided by M2 money supply — measures how efficiently money circulates in the economy. Declining velocity means more money is needed to generate the same output, a deflationary signal. Rising velocity can amplify inflation. Quarterly frequency, critical context for M2 growth interpretation.

Output

Returns a JSON array of quarterly observations, each containing the date, raw velocity value (GDP/M2 ratio), month-over-month and year-over-year absolute and percentage changes, 12-month and 5-year z-scores, 5-year percentile rank, 3-month and 12-month rolling averages, and a binary flag indicating whether the value is above its long-run trend.

Example use cases

Inflation regime assessment

“Get me the M2 velocity data from StationFX for the last 3 years — I need the quarterly values, year-over-year percent changes, and z-scores so I can judge whether rising money supply is actually translating into inflation pressure.”

Monetary policy research report

“Fetch the full history of M2 velocity from StationFX — I want the raw values, trend flags, and 5-year percentile ranks so I can include a chart in my quarterly macro research note on Fed policy effectiveness.”

Deflationary signal monitoring

“Check the latest M2 velocity reading on StationFX and tell me if it's below its long-run trend and how the z-score compares to the past 5 years — I'm trying to detect early deflationary signals.”

Technical details

Endpoint

GEThttps://stationfx.com/economic-data/money-supply/velocity-of-m2-money-stock?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need quarterly GDP/M2 velocity data with pre-computed momentum, trend, and z-score statistics — especially to contextualize M2 growth signals, assess inflationary or deflationary regimes, or build macro dashboards without performing your own calculations. Prefer it over raw Federal Reserve data sources when you want normalized, agent-ready output including percentile ranks and rolling averages in a single call.

Side effects

Invalid date format returns a 400 error
Date range with no quarterly data available returns an empty array
Unsupported fmt value causes a parameter validation error
Requesting fields not available for this series returns partial or error response
Service downtime or upstream data feed delay may return stale or unavailable data

Input

Schema · Request body

Field	Type	Description
inputrequired	object
output	object

Output

Schema · Response

{
  "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": "Q",
      "source_key": "M2V"
    }
  }
}

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