Fear and Greed Index Tracker — API Integration & OpenData Solutions

Real-Time Sentiment Score Feed

The app maintains a live sentiment score (0–100) for both the stock market and the crypto market, refreshed on the underlying source's schedule. Our integration wraps this into a polling or push feed that delivers the current score, category label (Extreme Fear / Fear / Neutral / Greed / Extreme Greed), and Unix timestamp — ideal for embedding in trading dashboards, signal services, or news tickers without building your own aggregation layer.

Seven-Indicator Sub-Data Extraction

Beyond a single composite number, the app's Professional Insights module surfaces seven discrete CNN indicators: Market Momentum (S&P 500 vs. its 125-day moving average), Stock Price Strength (net new 52-week highs vs. lows on the NYSE), Stock Price Breadth (McClellan Volume Summation Index), Put/Call Options (5-day average ratio), Market Volatility (VIX), Safe Haven Demand (20-day stock/bond return spread), and Junk Bond Demand (yield spread). Each field is extractable as a named JSON property for use in multi-variable risk scoring and portfolio stress tests.

Historical Time-Series & Distribution API

The Trend Timeline and Distribution Analysis features expose up to 12 months of daily index values. This historical time-series is the foundation for quantitative backtesting: platforms like QuantConnect have documented strategies that buy S&P 500 exposure when the score falls below 25 (Extreme Fear) and liquidate when it exceeds 75 (Extreme Greed). Our integration exports this data in JSON arrays or CSV-compatible format, ready to load into pandas, InfluxDB, or any time-series data store.

Stage-Change Alert & Webhook Integration

Introduced in the app's 2024 update, Custom Threshold Alerts let users define personal "alert when below X / above Y" trigger levels for both stock and crypto indices. Our integration maps these triggers to outbound webhook calls — when the index crosses a defined boundary, a POST payload is dispatched to your endpoint with the new score, the previous score, the transition direction, and the asset class. This pattern directly powers automated position-sizing rules and risk-off signals in algo trading systems.

1-Year Heatmap & Extreme Event Log Export

The 1-Year Heatmap renders daily sentiment as a color-coded matrix across the full calendar year. Exported as a structured array (date → score → category), this data feeds BI tools (Grafana, Tableau, Power BI) for visual compliance audits, seasonal pattern analysis, and investor-facing sentiment reports. The Extreme History feature additionally provides a log of every Extreme Fear and Extreme Greed event with date and magnitude, enabling anomaly-detection pipelines and stress-scenario backtests.

Widget Refresh Data & Streak Sync

The app's home-screen widgets (stock and crypto) refresh autonomously via background update cycles — the 2024 release added Auto Dark Mode adaptation and Background Opacity Control. Our integration mirrors the widget data contract: current score, category, and trend direction on a configurable interval (hourly or custom). The Streak Tracker (current consecutive-day streak vs. 1-year record) is also exposed as a structured field, useful for building user-engagement modules or gamified investment dashboards that reward consistent sentiment monitoring.

1. Fetch current Crypto Fear & Greed (Alternative.me)

// GET current crypto sentiment score
GET https://api.alternative.me/fng/?limit=1&format=json

// Response (simplified)
{
  "name": "Fear and Greed Index",
  "data": [
    {
      "value": "42",
      "value_classification": "Fear",
      "timestamp": "1713830400",
      "time_until_update": "63847"
    }
  ],
  "metadata": { "error": null }
}

// Use in Python:
import requests
resp = requests.get(
    "https://api.alternative.me/fng/",
    params={"limit": 1, "format": "json"}
)
data = resp.json()["data"][0]
score = int(data["value"])        # e.g. 42
category = data["value_classification"]  # "Fear"

2. Fetch CNN Stock F&G with Sub-Indicators

// Protocol analysis: extract CNN stock sentiment data
// Source endpoint: production.dataviz.cnn.io/index/
//                  fearandgreed/graphdata/{start_date}

GET /api/v1/fgi/stock/current
Authorization: Bearer <SESSION_TOKEN>

// Normalized response (our API schema):
{
  "score": 58,
  "category": "Greed",
  "updated_at": "2025-04-22T21:00:00Z",
  "sub_indicators": {
    "market_momentum":   { "value": 71, "signal": "Greed" },
    "stock_strength":    { "value": 55, "signal": "Neutral" },
    "stock_breadth":     { "value": 63, "signal": "Greed" },
    "put_call_ratio":    { "value": 48, "signal": "Fear" },
    "market_volatility": { "value": 54, "signal": "Neutral" },
    "safe_haven_demand": { "value": 61, "signal": "Greed" },
    "junk_bond_demand":  { "value": 67, "signal": "Greed" }
  }
}

3. Historical Export & Stage-Change Webhook

// Historical time-series export (1 month of daily scores)
GET /api/v1/fgi/stock/history
  ?from=2025-03-01&to=2025-04-01
  &format=json
Authorization: Bearer <SESSION_TOKEN>

// Response: array of daily snapshots
{
  "asset_class": "stock",
  "data": [
    { "date": "2025-03-01", "score": 34, "category": "Fear" },
    { "date": "2025-03-02", "score": 31, "category": "Fear" },
    ...
  ]
}

// Stage-change webhook payload (POST to your endpoint):
{
  "event": "stage_change",
  "asset_class": "crypto",
  "previous_score": 74,
  "previous_category": "Greed",
  "new_score": 81,
  "new_category": "Extreme Greed",
  "direction": "up",
  "triggered_at": "2025-04-22T14:30:00Z"
}

Compliance & Privacy

Fear and Greed Index data integration operates in the financial data and market information domain. Key regulatory and privacy considerations for integrators:

• GDPR (EU/EEA) — User notification preferences, device identifiers stored in the app, and usage analytics may be subject to GDPR consent and data-minimization requirements for users in the European Economic Area. Our integration extracts only market sentiment scores and sub-indicators — no personal data or PII is involved in the core data pipeline.
• SEC / FINRA (US) — Sentiment indices are classified as supplementary market information, not investment advice. Any platform embedding fear & greed data for US users should include appropriate disclaimers consistent with SEC guidance on non-discretionary market data display. The app itself states: "this app provides market information for educational purposes and is NOT financial advice."
• CCPA (California) — App analytics and device-level data are subject to California Consumer Privacy Act disclosure requirements for US-based users. Integration outputs are anonymized aggregate metrics, outside CCPA's personal-data scope.
• Data Attribution — CNN Business and Alternative.me are the upstream data sources. Commercial re-distribution of their data requires reviewing each provider's terms of service; our protocol analysis and integration layer handles normalization on top of authorized or publicly documented endpoints.

Data Flow & Architecture

The integration pipeline follows a straightforward open-data ingestion pattern:

1. Source Fetch — Scheduled pull from CNN dataviz endpoint (stock sub-indicators) and Alternative.me API (crypto score), on their native update cadences (daily for CNN, daily + intraday checks for Alternative.me).
2. Normalization Layer — Raw responses parsed into a unified schema: score, category, asset_class, sub_indicators[], updated_at. Sub-indicators standardized to a 0–100 scale with named keys.
3. Storage — Time-series database (InfluxDB or PostgreSQL with TimescaleDB extension) stores each daily snapshot keyed by (date, asset_class). Event log table records stage transitions for webhook dispatch.
4. API Gateway — REST endpoints expose current score, historical array, sub-indicators, and event log. Optional webhook subscriptions push stage-change events to registered consumer URLs.
5. Consumer Apps — Trading bots, portfolio dashboards, BI tools (Grafana, Tableau), CMS platforms, and alert systems consume the API output without needing to build their own sentiment aggregation infrastructure.

Engagement workflow

1. Scope confirmation — Identify required endpoints (current score, historical, sub-indicators, webhooks), asset classes (stock, crypto, or both), and consumer platform constraints (1–2 days).
2. Protocol analysis & API design — Map source data endpoints, document update schedules, and draft the normalized response schema (2–3 business days).
3. Build & validation — Implement fetchers, normalizers, storage, and webhook dispatcher; run against live sources (3–6 business days).
4. Documentation & test delivery — OpenAPI spec, integration guide, code samples, and automated test suite (1–2 business days).
5. Typical first delivery — 6–12 business days total; complex multi-asset or real-time webhook setups may extend the timeline.

FAQ

What do you need from me to start?

Is the fear & greed data free to use?

Can I get intraday (more frequent than daily) data?