Balancer (BAL) Sentiment & Fear and Greed Index
As of July 18, 2026, Balancer's Nebula Fear & Greed Index is 27 (Fear), its social sentiment score is 64/100 (bullish), 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
Latest Balancer insights
The Balancer attacker has converted $48.7 million worth of Ethereum (ETH) into 617 Bitcoin (BTC). This significant asset conversion occurred amidst an ongoing liquidation, with the attacker reportedly retaining an additional 1,000 ETH.
A Balancer exploiter recently converted $120 million worth of Ethereum (ETH) into Bitcoin (BTC). This significant transaction was executed using ThorChain, a decentralized cross-chain liquidity protocol. The major movement of funds by the attacker has reportedly sent shockwaves throughout the cryptocurrency market.
The Balancer exploiter, responsible for a nearly $120 million theft, has reactivated after a five-month dormancy. The exploiter is currently laundering funds by swapping stolen ETH into BTC via THORChain. Over the past hour, approximately 1,100 ETH, valued at $2.55 million, has been moved and converted.
Frequently asked questions
What is Balancer's Fear & Greed Index?
Balancer's Nebula Fear & Greed Index is currently 27 out of 100, which is Fear. The index blends social sentiment, social interest, price momentum, volatility, and emotional intensity into a single 0–100 sentiment score, updated continuously.
Is Balancer bullish or bearish right now?
Balancer's social sentiment is currently bullish, with a sentiment score of 64/100 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 Balancer sentiment?
Nebula reads every relevant social post about Balancer 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.
