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BITCOIN FEAR AND GREED INDEX

What is the Bitcoin Fear and Greed Index?

This Bitcoin Fear and Greed Index is based upon five different measurements—market volatility, momentum and volume, social media sentiment, BTC Dominance, and Google Trends sentiment—in order to provide you with a clearer picture on the current crypto market feel and make it easier for you to sell at the top and buy at the bottom and not the other way around.

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REAL-TIME BTC FEAR AND GREED INDEX

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EXTREME FEAR

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MONTHLY HISTORICAL PERFORMANCE

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Historical Fear & Greed vs BTC Price Correlation Chart
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The Crypto Fear & Greed Index is a composite sentiment indicator that scores the market from 0 (Extreme Fear) to 100 (Extreme Greed) based on a weighted blend of six data sources: price volatility, market momentum and volume, social media signals, surveys, Bitcoin dominance, and Google Trends data. Each component is normalized and combined to produce a single number that reflects the prevailing emotional state of the crypto market.

The index is most useful as a contrarian signal. Historically, readings in the Extreme Fear zone (0–25) have coincided with capitulation events and attractive long-term entry points. Readings in the Extreme Greed zone (75–100) have often appeared near cycle tops, when the market is over-leveraged and expectations are stretched. Being greedy when others are fearful, and cautious when others are greedy, is the classic framework most traders apply to this index.

Day-to-day swings in the index are less useful than the trend direction and duration. A market that has been in Extreme Fear for several weeks carries different implications than a single-day dip into that zone. Similarly, extended greed periods that persist without a reset can signal that sentiment is becoming structurally over-extended rather than just momentarily elevated.

Like all sentiment tools, the index has limitations — it cannot predict timing, and components such as social media signals can be gamed or distorted during viral events. Use it alongside price action, on-chain data such as MVRV Z-Score and NUPL, and derivatives signals like funding rates and long/short ratios to form a complete picture of market conditions.