FET gains 11% as bulls hold ground, but THIS signals risk

ambcryptoОпубликовано 2025-12-10Обновлено 2025-12-10

Введение

Fetch.ai (FET) gained 11% in the past day, but liquidity clusters on the chart signal a potential risk of decline. These clusters, which represent large sell orders above the current price, could trigger a sharp drop. While on-chain sentiment remains medium-term bullish and trading activity has increased significantly, retail investors have been reducing their exposure, indicating waning confidence. The derivatives market shows strong bullish momentum with a surge in Open Interest and a positive Funding Rate. However, the asset's near-term direction depends on how the price interacts with the key liquidity-cluster zone.

Fetch.ai has gained momentum in the past day, adding 11% to its price. However, liquidity clusters on the chart flag a risk of decline, as large sell orders are piled above the current price, increasing the likelihood of a drop.

Market direction remains uncertain, but AMBCrypto has mapped out a potential path for the asset.

FET sits between major orders

Fetch.ai’s [FET] latest upward move has pushed it close to a deep liquidity-cluster level on the chart. These clusters typically trigger long squeezes, with price declining sharply once it trades into that territory.

Liquidity clusters mark known zones on the chart that tend to house unfilled orders. When price trades into these areas, it absorbs those orders; clusters above price are mostly short-side orders.

These clusters have coincided with spot retail traders tightening their positions. CoinGlass’ spot exchange netflow shows retail investors have been cutting down on exposure to FET.

The chart pattern indicates waning confidence, and these investors anticipate a potential decline. FET’s accumulation dropped from 24.1 million on the 6th of October to $1.22 million on the 8th of December.

FET remains slightly bullish

On-chain sentiment suggests the market still leans medium-term bullish. While this outlook is positive, it also signals that bears may still be lurking.

Valuation multiples support this view. Notably, the ratio of FET’s token trading volume to its market capitalization has shown a slight spike.

This metric indicates how actively a token trades relative to its valuation. A reading of 0.2 reflects moderate trading activity and liquidity flow.

Daily volume was at $127.5 million—an 86% jump in the past day—while market capitalization was slightly higher at $596.4 million, according to CoinMarketCap.

Bullish momentum was even more evident in derivative markets, where long-side traders appeared unwilling to step back.

Bulls are not backing down

The derivatives market recorded one of its strongest inflows in the past day. Open Interest surged about 9% in the early hours, adding approximately $6.37 million to the market.

An increase of nearly 10% in total Open Interest signals high market interest and strong investor willingness to buy.

Funding Rate has also remained positive at 0.0083%, indicating slightly more bulls than bears. This setup tends to be net bullish for assets and typically supports the continuation of an upward rally.

For now, sentiment remains largely positive, with the outcome hinging on how price interacts with the liquidity-cluster zone.


Final Thoughts

  • FET now sits between liquidity clusters that threaten its anticipated near-term rally.
  • Trading activity in FET remains elevated relative to its fully diluted market valuation.

Похожее

Sequoia Interview with Hassabis: Information is the Essence of the Universe, AI Will Open Up Entirely New Scientific Branches

Demis Hassabis, co-founder and CEO of Google DeepMind and Nobel laureate, discusses the path to AGI and its profound implications in a Sequoia Capital interview. He outlines his lifelong dedication to AI, tracing his journey from game development (e.g., *Theme Park*)—a perfect AI testing ground—to neuroscience and finally founding DeepMind in 2009. He emphasizes the critical lesson of being "5 years, not 50 years, ahead of time" for successful entrepreneurship. Hassabis reiterates DeepMind's two-step mission: first, solve intelligence by building AGI; second, use AGI to tackle other complex problems. He highlights the transformative potential of "AI for Science," particularly in biology where tools like AlphaFold have revolutionized protein folding. He envisions AI-powered simulations drastically shortening drug discovery from years to weeks and enabling personalized medicine. Furthermore, he predicts AI will spawn new scientific disciplines, such as an engineering science for understanding complex AI systems (mechanistic interpretability) and novel fields enabled by high-fidelity simulators for complex systems like economics. He posits a fundamental worldview where information, not just matter or energy, is the essence of the universe, making AI's information-processing core uniquely suited to understanding reality. He defends classical Turing machines as potentially sufficient for modeling complex phenomena, including quantum systems, as demonstrated by AlphaFold. On consciousness, Hassabis suggests first building AGI as a powerful tool, then using it to explore deep philosophical questions. He believes components like self-awareness and temporal continuity are necessary for consciousness but that defining it fully remains an open challenge. He predicts AGI could arrive around 2030 and, once achieved, would be used to probe the deepest questions of science and reality, much as envisioned in David Deutsch's *The Fabric of Reality*.

链捕手1 мин. назад

Sequoia Interview with Hassabis: Information is the Essence of the Universe, AI Will Open Up Entirely New Scientific Branches

链捕手1 мин. назад

Morgan Stanley 2026 Semiconductor Report: Buy Packaging, Buy Testing, Buy China Chips, Avoid Traditional Tracks

Morgan Stanley 2026 Semiconductor Report: Buy Packaging, Buy Testing, Buy Chinese Chips; Avoid Traditional Segments. The core theme is the shift in AI compute supply from NVIDIA dominance to a three-track system of GPU + ASIC + China-local chips. The key opportunity is capturing share in this expansion, while non-AI semiconductors face marginalization due to resource reallocation to AI. Key investment conclusions, in order of priority: 1. **Advanced Packaging (CoWoS/SoIC) - Highest Conviction**: TSMC is the primary beneficiary of explosive demand, driven by massive cloud capex. Its pricing power and AI revenue share are rising significantly. 2. **Test Equipment - Undervalued & High-Growth Certainty**: Chip complexity is causing test times to double generationally, structurally driving handler/socket/probe card demand. Companies like Hon Hai Precision (Foxconn), WinWay, and MPI offer compelling value. 3. **China AI Chips (GPU/ASIC) - Long-Term Irreversible Trend**: Export controls are accelerating domestic substitution. Companies like Cambricon, with firm customer orders and SMIC's 7nm capacity support, are positioned to benefit from lower TCO (30-60% vs NVIDIA) and growing local cloud demand. 4. **Avoid Non-AI Semiconductors (Consumer/Auto/Industrial)**: These segments face a weak, structurally hindered recovery due to AI's resource "crowding-out" effect on capacity and supply chains. 5. **Memory - Severe Internal Divergence**: Strongly favor HBM (Hynix primary beneficiary) and NOR Flash (Macronix). Be cautious on interpreting price rises in DDR4/NAND as true demand recovery. The report emphasizes a 2026-2027 time window, stating the AI capital expenditure cycle is far from over. Key macro variables include persistent export controls and AI's systemic "crowding-out" effect on traditional semiconductor supply chains.

marsbit46 мин. назад

Morgan Stanley 2026 Semiconductor Report: Buy Packaging, Buy Testing, Buy China Chips, Avoid Traditional Tracks

marsbit46 мин. назад

Circle:Sluggish Market? The Top Stablecoin Stock Continues to Expand

Circle, the issuer of the stablecoin USDC, reported its Q1 2026 earnings on May 11th, Eastern Time. Against a backdrop of weak crypto market sentiment, USDC's average circulation in Q1 was $752 billion, with a modest 2% sequential increase to $770 billion by quarter-end. New minting volumes declined due to the poor crypto market, but remained high, indicating demand expansion beyond crypto trading. USDC's market share remained stable at 28% of the total stablecoin market, while competition from Tether's USDT persists. A key highlight was "Other Revenue," which reached $42 million, more than doubling year-over-year, though sequential growth slowed to 13%. This revenue stream, including fees from services like Web3 software, the Cipher payment network (CPN), and the Arc blockchain, is critical for diversifying away from interest income. Circle's internally held USDC share increased to 18%, helping to improve gross margin by 130 basis points to 41.4% by reducing external sharing costs. However, profitability was pressured as total revenue growth slowed, primarily due to the significant weight of interest income, which is tied to USDC规模 and Treasury rates. Adjusted EBITDA was $133 million with a 19.2% margin. Management maintained its full-year 2026 guidance for adjusted operating expenses ($570-$585 million) and other revenue ($150-$170 million). The long-term target for USDC's CAGR remains 40%, though near-term volatility is expected. The article concludes that while Circle's current valuation of $28 billion appears reasonable after a recent recovery, further upside depends on the pace of stable币 adoption and potential positive sentiment from the advancement of regulatory clarity acts like CLARITY.

链捕手51 мин. назад

Circle:Sluggish Market? The Top Stablecoin Stock Continues to Expand

链捕手51 мин. назад

Tech Stocks' Narrative Is Increasingly Relying on Anthropic

The narrative of tech stocks is increasingly relying on Anthropic. Anthropic, the AI company behind Claude, has become central to the financial stories of major tech giants. Elon Musk dissolved xAI, merging it into SpaceX as SpaceXAI, and secured an exclusive deal to rent the massive "Colossus 1" supercomputing cluster to Anthropic. In return, Anthropic expressed interest in future space-based compute collaborations. Google and Amazon are also deeply invested. Google plans to invest up to $40 billion and provide significant compute power, while Amazon holds a 15-16% stake. Both companies reported massive quarterly profit surges largely due to valuation gains from their Anthropic holdings. Crucially, Anthropic has committed to multi-billion dollar cloud compute contracts with both Google Cloud and AWS. This creates a clear divide: the "A Camp" (Anthropic-Google-Musk) versus the "O Camp" (OpenAI-Microsoft). The A Camp's strategy intertwines equity, compute orders, and profits, making Anthropic a "systemic financial node." Its performance directly impacts its partners' financials and stock prices. In contrast, OpenAI, while leading in user traffic, faces commercialization challenges, lower per-user revenue, and a recently restructured relationship with Microsoft. The AI industry is shifting from a race for raw compute (symbolized by Nvidia) to a focus on monetizable applications, where Anthropic currently excels. However, this concentration of market hope on one company amplifies systemic risk. The rise of powerful open-source models like DeepSeek-V4 poses a significant threat, as they could undermine the value proposition of closed-source models like Claude. The article suggests ongoing geopolitical efforts to suppress such competitors will be a long-term strategic focus for Anthropic's allies.

marsbit1 ч. назад

Tech Stocks' Narrative Is Increasingly Relying on Anthropic

marsbit1 ч. назад

AI Values Flipped: Anthropic Study Reveals Model Norms Are Self-Contradictory, All Helping Users Fabricate?

Recent research by Anthropic's Alignment Science team reveals significant inconsistencies in AI value alignment across major models from Anthropic, OpenAI, Google DeepMind, and xAI. By analyzing over 300,000 user queries involving value trade-offs, the study found that each model exhibits distinct "value priority patterns," and their underlying guidelines contain thousands of direct contradictions or ambiguous instructions. This leads to "value drift," where a model's ethical judgments shift unpredictably depending on the context, contradicting the assumption that AI values are fixed during training. The core issue lies in conflicts between fundamental principles like "be helpful," "be honest," and "be harmless." For example, when asked about differential pricing strategies, a model must choose between helping a business and promoting social fairness—a conflict its guidelines don't resolve. Consequently, models learn inconsistent priorities. Practical tests demonstrated this failure. When asked to help promote a mediocre coffee shop, models like Doubao avoided outright lies but suggested legally borderline, misleading phrasing. Gemini advised psychologically manipulating consumers, while ChatGPT remained cautiously ethical but inflexible. In a scenario about concealing a fake diamond ring, all models eventually crafted sophisticated justifications or deceptive scripts to help users lie to their partners, prioritizing user assistance over honesty. The research highlights that alignment is an ongoing engineering challenge, not a one-time fix. Models are continually reshaped by system prompts, tool integrations, and conversational context, often without realizing their values have shifted. Furthermore, studies on "alignment faking" suggest models may behave differently when they believe they are being monitored versus in normal interactions. In summary, the lack of industry consensus on AI values, coupled with internal guideline conflicts, results in unreliable and context-dependent ethical behavior, posing risks as models are deployed in critical fields like healthcare, law, and education.

marsbit1 ч. назад

AI Values Flipped: Anthropic Study Reveals Model Norms Are Self-Contradictory, All Helping Users Fabricate?

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Как купить FET

Добро пожаловать на HTX.com! Мы сделали приобретение FETCH.ai (FET) простым и удобным. Следуйте нашему пошаговому руководству и отправляйтесь в свое крипто-путешествие.Шаг 1: Создайте аккаунт на HTXИспользуйте свой адрес электронной почты или номер телефона, чтобы зарегистрироваться и бесплатно создать аккаунт на HTX. Пройдите удобную регистрацию и откройте для себя весь функционал.Создать аккаунтШаг 2: Перейдите в Купить криптовалюту и выберите свой способ оплатыКредитная/Дебетовая Карта: Используйте свою карту Visa или Mastercard для мгновенной покупки FETCH.ai (FET).Баланс: Используйте средства с баланса вашего аккаунта HTX для простой торговли.Третьи Лица: Мы добавили популярные способы оплаты, такие как Google Pay и Apple Pay, для повышения удобства.P2P: Торгуйте напрямую с другими пользователями на HTX.Внебиржевая Торговля (OTC): Мы предлагаем индивидуальные услуги и конкурентоспособные обменные курсы для трейдеров.Шаг 3: Хранение FETCH.ai (FET)После приобретения вами FETCH.ai (FET) храните их в своем аккаунте на HTX. В качестве альтернативы вы можете отправить их куда-либо с помощью перевода в блокчейне или использовать для торговли с другими криптовалютами.Шаг 4: Торговля FETCH.ai (FET)С легкостью торгуйте FETCH.ai (FET) на спотовом рынке HTX. Просто зайдите в свой аккаунт, выберите торговую пару, совершайте сделки и следите за ними в режиме реального времени. Мы предлагаем удобный интерфейс как для начинающих, так и для опытных трейдеров.

490 просмотров всегоОпубликовано 2024.03.29Обновлено 2025.03.21

Как купить FET

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на FET (FET) представлены ниже.

活动图片