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Fear and Greed Index

Sentiment:

KOL Calls

Long/Short Calls

Mindshare:

Intelligence

Emotions

Social Momentum

Feed:

Conviction Index

Followers

Volume ($)

Volatility

Mcap vs BTC

Sentiment Timeframes

Twenty One Capital (XXI) Sentiment & Fear and Greed Index

As of July 21, 2026, Twenty One Capital's Nebula Fear & Greed Index is 0 (Extreme Fear), it holds 0.00% of crypto social mindshare. These signals are computed by Nebula from social posts across crypto Twitter/X and other sources, scored with large language models rather than keyword counts.

Updated continuously · Source: Nebula

Fear & Greed0 · Extreme Fear
Mindshare0.00%

Latest Twenty One Capital insights

Jack Mallers Steps Down as Twenty One Capital CEOJul 21, 2026

Jack Mallers stepped down as CEO of Twenty One Capital, a Bitcoin-focused financial firm. Raphael Zagury was appointed as the new CEO.

Tether Proposes Merger to Form Public Bitcoin PlatformApr 29, 2026

Tether Investments has proposed a three-way merger involving Twenty One Capital (NYSE: XXI), Strike, and Elektron Energy. The strategic combination aims to create a comprehensive, publicly listed Bitcoin-native platform. This move seeks to merge a public entity with a Bitcoin payment platform, founded by Jack Mallers, and an energy company.

Frequently asked questions

What is Twenty One Capital's Fear & Greed Index?

Twenty One Capital's Nebula Fear & Greed Index is currently 0 out of 100, which is Extreme Fear. The index blends social sentiment, social interest, price momentum, volatility, and emotional intensity into a single 0–100 sentiment score, updated continuously.

Is Twenty One Capital bullish or bearish right now?

Nebula scores Twenty One Capital's social sentiment as bullish, bearish, or mixed based on LLM analysis of the crypto social conversation. Sentiment reflects market mood, not financial advice.

How does Nebula measure Twenty One Capital sentiment?

Nebula reads every relevant social post about Twenty One Capital across crypto Twitter/X and other sources and scores it with large language models — capturing bullish/bearish tone, emotion, and who is speaking (from retail to smart money) — rather than counting keywords.