StationFX CBOE Volatility Index (VIX)

x402

StationFX CBOE Volatility Index (VIX) 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 daily CBOE VIX time-series data with derived statistics for risk sentiment analysis, hedging signals, and market regime detection.

Price / call$0.005

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Success—

StatusUnknown

How this service works

CBOE measure of expected 30-day volatility in the S&P 500, derived from options prices. The market's fear gauge. Spikes during crises and risk-off events. Use for risk sentiment analysis, hedging signal generation, and regime detection. Daily frequency with full history.

Output

Returns an array of daily observations, each containing the raw VIX value, month-over-month and year-over-year absolute and percentage changes, z-scores relative to trailing 12 months and 5 years, percentile rank over trailing 5 years, 3-month and 12-month rolling averages, and a binary above-trend flag. Optionally returned in compact 'toon' format for agent-friendly consumption.

Example use cases

Hedging signal before earnings season

“Check the current VIX level and its 5-year percentile rank — is fear elevated enough to justify buying portfolio protection heading into this earnings season?”

Crisis regime detection for portfolio

“Pull the VIX daily history from January 2020 to December 2020 so I can see how the fear gauge spiked during COVID and how long the elevated volatility regime lasted.”

Risk sentiment dashboard update

“Get me today's VIX reading along with the rolling 3-month average and whether it's above the long-run trend — I need it in compact toon format for my morning risk dashboard.”

Technical details

Endpoint

GEThttps://stationfx.com/economic-data/financial-conditions/cboe-volatility-index-vix?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need daily CBOE VIX data enriched with statistical context (z-scores, percentile ranks, rolling averages, trend signals) rather than a raw price feed. Ideal for agents performing risk regime detection, hedging signal generation, or macro financial conditions analysis where historical context and derived statistics matter. Prefer over raw market data APIs when pre-computed analytics are needed without additional transformation.

Side effects

Invalid date range (date_from after date_to) may return empty data or error
Requesting dates before VIX history begins returns no data
Invalid fmt enum value returns format error
Network or payment (x402) failure returns no response
Requesting future dates returns no 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": "D",
      "source_key": "VIXCLS"
    }
  }
}

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