Crypto Fear and Greed Index Drops to Extreme Fear at 9

TheNewsCryptoОпубліковано о 2026-02-09Востаннє оновлено о 2026-02-09

Анотація

The Crypto Fear and Greed Index by CoinMarketCap has dropped to 9, indicating a state of "extreme fear" in the market sentiment. This marks a significant decline from 15 a week ago and 41 a month prior. The index hit a yearly low of 5 on February 6. Despite the persistently high market cap, sentiment has shifted aggressively. Bitcoin is trading around $70,505, Ethereum at $2,096, and Solana between $86.2 and $88.6. The overall crypto market cap has rebounded to over $2.4 trillion. The index, which ranges from 0 (extreme fear) to 100 (extreme greed), is a widely referenced tool for quantifying market sentiment.

The sentiment of crypto has changed to panic, and the gauge of CoinMarketCap has turned red now. The CMC Crypto Fear and Greed Index of the platform is at 9, taking it to an extreme fear situation.

One week before, the number was 15 and was neutral with 41 in the last month. On February 8, the score stood at 8, and on February 6, the score hit a yearly low, sitting at 5. It also highlighted how aggressively sentiment has shifted regardless of a persistently high market cap backdrop.

CoinMarketCap has mentioned that the tool is a powerful tool for analysing market sentiment to aid investors in informing crypto investment decisions, referring to it as the most trustworthy measure of total crypto market sentiment and the number 1, most quoted and most trusted index of its kind among mainstream financial outlets.

The Significant Pricing

The index contains a 0-100 scale, and here the lower value shows an extreme fear state and the higher value shows an extreme greed state, successfully quantifying what many traders only feel subjectively in price action.

As the rollout note mentions, this revolutionary index offers a broad-ranging and quantifiable assessment of fear and greed for the overall cryptocurrency industry. The spot markets show that Bitcoin trades around $70,505 with around $42.8 billion in 24-hour volume.

Ethereum is now trading at $2,096 on around $20.9 billion in turnover. The price of Solana sits at $86.2 and $88.6. The pricing situation aligns with a wider rebound in virtual assets, with BTC recently reclaiming the $71,000 area after last week’s failure and overall crypto market capitalisation shifting back over $2.4 trillion. CoinMarketCap makes it clear that the Fear and Greed Index is not a clear indicator in itself but can offer a useful measure of the market sentiment.

Highlighted Crypto News Today:

Japan Election Result Drive Possible Bull Run for Crypto Prices

TagsCoinMarketCapcrypto fear and greedCryptocurrency

Пов'язані питання

QWhat is the current reading of the CoinMarketCap Crypto Fear and Greed Index and what does it signify?

AThe current reading is 9, which signifies an 'Extreme Fear' situation in the market.

QHow does the current Fear and Greed Index reading compare to its value from one week ago and one month ago?

AOne week ago, the index was at 15 (Neutral), and one month ago it was at 41.

QWhat is the purpose of the Crypto Fear and Greed Index according to CoinMarketCap?

AAccording to CoinMarketCap, it is a powerful tool for analyzing market sentiment to aid investors in making crypto investment decisions, and it is considered the most trustworthy and quoted measure of total crypto market sentiment.

QWhat do the values on the 0-100 scale of the index represent?

AOn the 0-100 scale, a lower value indicates an extreme fear state, while a higher value indicates an extreme greed state.

QWhat was the approximate price of Bitcoin and the total crypto market capitalization mentioned in the article?

ABitcoin was trading around $70,505, and the overall crypto market capitalization had shifted back over $2.4 trillion.

Пов'язані матеріали

Crypto Miners' Big AI Gamble: Valuations Enter Differentiation Stage, Comeback Fight Proves Tough

Crypto Mining Firms' AI Bet: Valuation Divergence and a Challenging Transformation Facing declining profitability in crypto mining, mining companies are pivoting to AI infrastructure, capitalizing on their existing power resources, land, and data center expertise to offer GPU compute power. This transition narrative has boosted their stock prices significantly, with firms like Hut 8 and Bitfarms seeing gains over 100% year-to-date, far outpacing Bitcoin. This has led to a market valuation split, with pioneers like CoreWeave reaching a $62.8B market cap, while others remain below $5B. The market currently prioritizes growth potential over short-term profits, which remain under pressure due to heavy capital expenditures for AI build-outs and crypto asset volatility. However, the transformation is a high-stakes gamble. Bitcoin mining profitability is shrinking, with the average production cost around $63,707 and miner margins contracting. While AI offers a more lucrative long-term path, it requires massive investment—estimated at a $500B near-term funding gap. Success now hinges on execution: delivering on contracted power capacity, securing quality tenants like major cloud providers, and managing the immense financial burden. The valuation focus is shifting from mere power capacity to project delivery, future cash flows, and tenant quality, making this a difficult but critical turnaround attempt.

链捕手5 хв тому

Crypto Miners' Big AI Gamble: Valuations Enter Differentiation Stage, Comeback Fight Proves Tough

链捕手5 хв тому

Analysis of the Latest Portfolio Adjustment by the "Top Player" in the U.S. Stock Market: $9 Billion Short on NVIDIA, Shifting Focus to Power and Memory Sectors

AI investor Leopold Aschenbrenner has made a significant portfolio shift, taking a $9 billion nominal short position against top AI infrastructure stocks like NVIDIA, ASML, and Oracle. Simultaneously, he is redirecting capital towards what he sees as the next critical bottlenecks in the AI boom: power, memory, and data center networking, alongside private investments in AI model companies like Anthropic. This move is interpreted not as a call that the AI bubble has burst, but as a rotation within the infrastructure stack. The analysis highlights NVIDIA's recent $25 billion bond issuance as a potential signal, questioning why a cash-rich company would seek external debt despite high profits and increased dividends/buybacks. The core investment thesis is that the initial, crowded "picks and shovels" trade in semiconductors is maturing. The next wave of capital is expected to flow into the physical and logistical constraints of AI expansion: electricity supply, memory chip capacity, data center construction, and enabling technologies like optical networking (fiber) for high-bandwidth communication, where copper remains crucial for short distances. Aschenbrenner's substantial (approx. 20% of fund) private stake in Anthropic is noted as a key part of his strategy—investing directly in the "mine" (AI models) rather than just the "shovels." The discussion concludes that while certain segments may be overvalued, the overarching AI infrastructure demand driven by real product usage remains robust. The most promising long-term investments are seen in essential, non-sexy infrastructure—particularly energy and power companies—whose demand is viewed as a global constant irrespective of AI's cyclicality.

marsbit26 хв тому

Analysis of the Latest Portfolio Adjustment by the "Top Player" in the U.S. Stock Market: $9 Billion Short on NVIDIA, Shifting Focus to Power and Memory Sectors

marsbit26 хв тому

BIT Research: Liquidity is Disappearing, Will Bitcoin Replay the Bottoming Pattern of 2022?

The crypto market is currently in an adjustment phase driven by policy expectations and liquidity shifts. Despite a brief rebound fueled by geopolitical easing and SpaceX's strong IPO performance, unexpectedly hawkish signals from new Fed Chair Kevin Warsh have removed anticipated easing support. Concurrently, stablecoin liquidity is shrinking, with insufficient new capital inflows, pushing the market into a typically quiet summer period. Pricing lacks catalysts for a sustained rally. Daily trading volume has significantly contracted, stablecoin growth has slowed markedly, and the supportive effect of Strategy's (formerly MicroStrategy) STRC preferred stock-financed Bitcoin purchases is fading. Amid policy uncertainty, seasonal weakness, and liquidity contraction, Bitcoin faces near-term downward pressure. Warsh's hawkish pivot and refusal to provide a clear policy outlook have increased risk premiums, historically unfavorable for Bitcoin. Technically, the trend remains bearish below $73,700, with $62,446 as critical support. A break below could accelerate declines, though a prolonged consolidation phase, similar to 2022's bottoming process, is possible. Liquidity is a core constraint. Current daily volume is around $500 billion, roughly 25% of the peak during the July-Oct 2025 rally. The 12-month growth rates for USDT and USDC have fallen to ~20%, with 6-month growth near zero, indicating weak new inflows. Bitcoin ETF and Strategy-driven inflows have also weakened, with a 30-day rolling net outflow. With inflation at 4.2% above the Fed's target, combined hawkish policy, seasonal factors, and liquidity shortages challenge Bitcoin's ability to hold above $60,000. However, this adjustment phase may be forming a cyclical low this summer, potentially setting the stage for the next bull cycle.

marsbit55 хв тому

BIT Research: Liquidity is Disappearing, Will Bitcoin Replay the Bottoming Pattern of 2022?

marsbit55 хв тому

Who Makes the Best Use of Claude Code? The Answer Might Not Be Programmers

Claude Code Usage Report Summary (Based on ~400k sessions) Core Finding: In agentic programming with Claude Code, a clear division of labor has emerged: humans primarily decide *what* to build (planning decisions), while Claude decides *how* to build it (execution decisions). Key Insights: 1. **Effectiveness is not limited to programmers.** In code-generation tasks, success rates for users in non-technical fields (law, finance, management, research) are nearing those of software engineers. What matters most is the user's domain expertise and understanding of the problem to be solved. 2. **Domain expertise drives success and efficiency.** Sessions where users exhibited "expert" proficiency in the task's domain saw verified success rates double compared to "novice" sessions. Experts also delegated more work per instruction, with Claude executing more actions and producing more output. 3. **AI is amplifying, not replacing, domain knowledge.** Claude Code lowers the *implementation* barrier, not the *judgment* barrier. The value of knowing the "what" and "why" is increasing relative to just knowing the "how" to code. 4. **Usage is evolving.** Over a 7-month period (Oct '25 - Apr '26), the share of sessions for debugging halved, while use for software operations, data analysis, and non-code writing roughly doubled. The estimated economic value of typical tasks increased by ~25%. Conclusion: The data suggests coding agents are making programming background less critical for completing technical tasks. However, they reward and amplify deep domain understanding. The ability to successfully direct an AI agent stems more from mastery of a specific field than from coding skill itself. The primary gains come from being competent in a domain; deep specialization adds only marginal additional advantage. This may signal a shift where software creation becomes integrated into various professions.

marsbit1 год тому

Who Makes the Best Use of Claude Code? The Answer Might Not Be Programmers

marsbit1 год тому

Торгівля

Спот
Ф'ючерси
活动图片