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Fear and Greed Index

SENTIMENT:

KOL CALLS

Long/Short Calls

MINDSHARE:

Intelligence

Emotions

Social Momentum

FEED:

Cultiness Index

Followers

Volume ($)

Volatility

Mcap vs BTC

Sentiment Timeframes

eCash (XEC) Sentiment & Fear and Greed Index

As of July 14, 2026, eCash's Nebula Fear & Greed Index is 13 (Extreme Fear), its social sentiment score is 14/100 (bearish), 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 & Greed13 · Extreme Fear
Sentiment14/100
Mindshare0.00%
Price$0.0000058 -14.6%

Latest eCash insights

Truthcoin Forks Bitcoin to Create eCashMay 1, 2026

Truthcoin is initiating a hard fork of Bitcoin with the explicit goal of creating eCash. This significant development is being led by the project's founder, who was previously a Bitcoin maximalist. An interview has been conducted to explore the reasons behind this decision and the shift in their perspective.

eCash Hard Fork for Bitcoin Holders Pressures BlackRockApr 30, 2026

A new hard fork has been announced that will distribute eCash at a 1:1 ratio to Bitcoin holders. This development is reported to also place BlackRock under pressure.

Frequently asked questions

What is eCash's Fear & Greed Index?

eCash's Nebula Fear & Greed Index is currently 13 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 eCash bullish or bearish right now?

eCash's social sentiment is currently bearish, with a sentiment score of 14/100 based on how bullish or bearish the crypto social conversation is. Sentiment reflects the mood of the market, not price direction or financial advice.

How does Nebula measure eCash sentiment?

Nebula reads every relevant social post about eCash 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.