CNN Fear & Greed Index Scraper — Market Sentiment Score, History & Components

Scrape the CNN Fear & Greed Index as clean, structured JSON, CSV, Excel or XML: the current market-sentiment score and rating, a full historical timeline of daily readings, and every one of the component indicators behind the index. Track whether the market is in fear or greed, chart sentiment over time, and feed it straight into trading signals, dashboards and alerts. Fast and reliable, with no account to manage.

What does CNN Fear & Greed Index Scraper do?

This CNN Fear & Greed Index scraper turns market-sentiment data into a structured dataset. In one run it returns the headline index (score from 0–100 and its rating, from extreme fear to extreme greed), the day-by-day historical timeline for roughly the last year, and the current reading of each component indicator that drives the index. Use it to power sentiment dashboards, backtest strategies, build trading signals and monitor mood swings in the market, then export the results in any format the Apify platform supports.

What data can you scrape from the CNN Fear & Greed Index?

Data point	Description
Current score	Latest Fear & Greed Index value, 0 (extreme fear) to 100 (extreme greed).
Current rating	Sentiment label: extreme fear, fear, neutral, greed or extreme greed.
Timestamp	When the current reading was published (ISO-8601).
Previous close	The index value at the previous close.
Previous 1 week	The index value one week ago.
Previous 1 month	The index value one month ago.
Previous 1 year	The index value one year ago.
Historical timeline	One row per day: date, score and rating over the history window.
Component score	Current score for each indicator that makes up the index.
Component rating	Fear/greed rating for each component indicator.
Component name	Human-readable name of each indicator (e.g. Market Momentum, Safe Haven Demand).

The component indicators

The index is a composite of several market signals, and this scraper exposes each one's current reading:

• Market Momentum — the S&P 500 versus its moving average.
• Stock Price Strength — stocks hitting highs versus lows.
• Stock Price Breadth — trading volume in rising versus falling stocks.
• Put and Call Options — the balance of bearish versus bullish options.
• Market Volatility — the VIX and its moving average.
• Junk Bond Demand — the spread between junk and investment-grade yields.
• Safe Haven Demand — the return on stocks versus Treasuries.

Use cases

• Trading signals — turn extreme-fear or extreme-greed readings into buy/sell triggers.
• Backtesting sentiment — join the historical timeline with price data to test contrarian strategies.
• Market dashboards — display a live fear/greed gauge alongside your other market widgets.
• Alerting — notify a channel when the index crosses a threshold or flips fear ↔ greed.
• Research & reporting — study how sentiment moved around events, earnings or selloffs.
• Component analysis — break the headline number down into its underlying indicators.
• Dataset building — feed structured sentiment data into BI tools, notebooks or models.

How to scrape CNN Fear & Greed Index data

1. Add CNN Fear & Greed Index Scraper to your Apify account and open its input.
2. Keep Include historical timeline on for the day-by-day history, or turn it off for just the current index.
3. Keep Include component indicators on to also get each underlying signal's current reading.
4. Optionally set a History start date (YYYY-MM-DD) to widen the timeline further back.
5. Click Run, then export the results as JSON, CSV, Excel or XML, or fetch them through the Apify API.

Input

{
  "includeHistorical": true,
  "includeComponents": true,
  "startDate": "",
  "proxyConfiguration": { "useApifyProxy": false }
}

Field	Description
includeHistorical	Add one row per day for the full index history (about a year of daily readings).
includeComponents	Add a current reading for each component indicator behind the index.
startDate	Optional. Widen the historical timeline back to this date, formatted YYYY-MM-DD.
proxyConfiguration	Optional Apify proxy settings for the run (not required).

Output

The dataset mixes three row types, each tagged with a type field so you can filter them apart: one index row, many historical rows, and one component row per indicator.

Current index (type: "index")

{
  "type": "index",
  "score": 41.86,
  "rating": "fear",
  "timestamp": "2026-09-04T23:59:43.000Z",
  "previousClose": 35.23,
  "previous1Week": 52.31,
  "previous1Month": 59.97,
  "previous1Year": 61.17,
  "componentCount": 9,
  "components": [
    { "key": "market_momentum_sp500", "name": "Market Momentum (S&P 500)", "score": 36.6, "rating": "fear", "timestamp": "2026-09-04T20:33:06.000Z" },
    { "key": "safe_haven_demand", "name": "Safe Haven Demand", "score": 26, "rating": "fear", "timestamp": "2026-09-04T19:59:55.000Z" }
  ],
  "scrapedAt": "2026-09-04T23:59:59.000Z"
}

Historical point (type: "historical")

{ "type": "historical", "date": "2026-09-04T23:59:43.000Z", "score": 41.86, "rating": "fear" }

Component reading (type: "component")

{ "type": "component", "component": "safe_haven_demand", "name": "Safe Haven Demand", "score": 26, "rating": "fear", "timestamp": "2026-09-04T19:59:55.000Z" }

Output schema

Field	Type	Description
type	string	Row type: index, historical or component.
score	number	Sentiment score, 0 (extreme fear) to 100 (extreme greed).
rating	string	Sentiment label: extreme fear, fear, neutral, greed or extreme greed.
timestamp	string (ISO date)	When the reading was published (index and component rows).
date	string (ISO date)	Date of a historical daily reading.
name	string	Human-readable component name (index summary and component rows).
component	string	Machine key of the component indicator (component rows).
previousClose	number	Index value at the previous close (index row).
previous1Week	number	Index value one week ago (index row).
previous1Month	number	Index value one month ago (index row).
previous1Year	number	Index value one year ago (index row).
componentCount	integer	Number of component indicators included (index row).
components	array	Summary array of each component's current score and rating (index row).
scrapedAt	string (ISO date)	Timestamp when the run collected the data.

Need more market data?

• CoinGecko Scraper — live crypto prices, market cap, volume and ATH/ATL.
• DefiLlama Scraper — DeFi protocols, yields, chains and stablecoins with TVL and APY.
• Yahoo Finance Scraper — live quotes and OHLCV history for stocks, ETFs, crypto and forex.
• TradingView Screener Scraper — screen stocks and crypto by dozens of technical and fundamental filters.

FAQ

Do I need an account or key? No login or key to manage — just set your inputs and click Run.

What does the score mean? The index runs 0–100: lower values mean fear (and, at the extreme, panic selling), higher values mean greed. The rating field labels the zone as extreme fear, fear, neutral, greed or extreme greed.

How far back does the history go? The default timeline covers roughly the last year of daily readings. Set a startDate to widen the window further back.

How fresh is the data? The current index, its comparison points and each component are pulled live at run time; every row carries a timestamp.

What are the component indicators? They are the underlying market signals the headline index blends together — market momentum, stock price strength and breadth, put/call options, market volatility, junk bond demand and safe-haven demand.

What export formats are available? JSON, CSV, Excel and XML, plus programmatic access through the Apify API.

Can I connect this to my other tools? The CNN Fear & Greed Index Scraper can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JavaScript/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.

Is this official CNN data? The data reflects the public CNN Business Fear & Greed Index, but this actor is an independent tool and is not affiliated with or endorsed by CNN.

Related Actors

• CoinGecko Scraper
• DefiLlama Scraper
• Binance Market Data Scraper
• CoinPaprika Scraper

Notes

Original clean-room implementation. Returns only public market-sentiment data; you are responsible for compliant use. Not affiliated with CNN; all trademarks belong to their respective owners.