StationFX Median Sales Price of New Houses Sold (U.S.)

x402

StationFX Median Sales Price of New Houses Sold (U.S.) is a paid API for AI agents from stationfx.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-02).

Returns monthly U.S. median sales price of newly constructed homes with derived metrics including MoM/YoY changes, z-scores, percentile ranks, and rolling averages.

Price / call$0.005

Seller volume →—

Success—

StatusUnknown

How this service works

Median price of newly constructed homes sold in the U.S. Measures affordability trends in the new home market. Sensitive to mortgage rates and construction costs. Monthly frequency, useful for housing affordability and consumer wealth analysis.

Output

Returns an array of monthly observations, each containing the raw median new home sales price value (in USD), month-over-month and year-over-year absolute 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 (1 or 0).

Example use cases

Housing affordability trend analysis

“Get me the U.S. median new home sales price data from January 2022 to today, including year-over-year percent changes and the 5-year z-score, so I can assess how affordability has shifted since rates started rising.”

Real estate investment thesis check

“What's the latest monthly median price for newly constructed homes in the U.S., and is it above or below the long-run trend? Include the 5-year percentile rank.”

Macroeconomic dashboard update

“Fetch the last 24 months of U.S. median new house sales price data with rolling 3-month and 12-month averages in compact toon format for my macro dashboard.”

Technical details

Endpoint

GEThttps://stationfx.com/economic-data/housing/median-sales-price-of-new-houses-sold-for-the-united-states?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need U.S. new construction home price data with pre-computed derivatives (MoM, YoY, z-scores, percentile ranks, rolling averages) in a single call, rather than fetching raw Census Bureau or FRED data and computing statistics yourself. Ideal for housing affordability analysis, macro dashboards, real estate market monitoring, and consumer wealth trend assessments at monthly frequency.

Side effects

Invalid date format returns a 400-level error
date_from after date_to returns empty or error response
Requesting fields not in the schema returns unknown field error
Payment not completed (x402) results in 402 Payment Required response
Dates outside available historical range return empty data array

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": "MSPUS"
    }
  }
}

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