10x Research: биткоин продолжит двигаться в широком диапазоне — период «только лонг» закончился

cryptonews.ruPublicado a 2025-02-16Actualizado a 2025-04-16

Ралли биткоина сменяется фазой длительной консолидации, а краткосрочные индикаторы указывают медвежьи перспективы, что противоречит мнению большинства криптосообщества. Такое заявление сделал глава исследовательского отдела 10x Research Маркус Тилен (Markus Thielen).

В то время как многие криптоаналитики прогнозируют новые исторические максимумы для биткоина к июню, Тилен в своем отчете от 14 апреля выразил скептицизм. Он подчеркнул, что данные блокчейна сигнализируют «скорее о медвежьей ситуации на рынке, чем о бычьей».

Краткосрочные индикаторы предупреждают о вершине рынка

По словам Тилена, краткосрочные индикаторы биткоина демонстрируют паттерны, «более характерные для вершины рынка или поздней фазы цикла, а не для ранних стадий нового бычьего ралли».

«В результате краткосрочные сигналы не соответствуют долгосрочным индикаторам, что подчеркивает расхождение в прогнозах рынка», — отметил Тилен.

«Рынок биткоина больше не является параболическим со стратегией исключительно на покупку, используемой розничными инвесторами», — добавил он, пояснив, что теперь криптовалюта «требует более сложного, финансово-ориентированного подхода».

Аналитик также указал, что «ралли биткоина за последний год было обусловлено не типичными спекулянтами от криптовалют, а долгосрочными держателями, стремящимися к диверсификации и придерживающимися стратегии покупки и удержания».

Движение цены биткоина может повторить паттерн 2024 года

Тилен подтвердил свою позицию, что биткоин может консолидироваться в течение длительного периода, как это было в 2024 году.

«Несмотря на наш осторожный оптимизм, мы считаем, что биткоин находится в широком диапазоне от $73 000 до $94 000 с небольшим подъемом», — заявил он.

В марте 2024 года биткоин достиг исторического максимума в $73 679, а затем перешел в фазу консолидации в диапазоне высотой около $20 000, выход из которого состоялся после победы Трампа на выборах в США в ноябре.

1-недельный график BTC/USD. Диапазон 2024 года

Текущая ситуация показывает, что динамика биткоина стала более сложной и менее предсказуемой, что требует тщательного анализа и взвешенного подхода от инвесторов.

Lecturas Relacionadas

AI Billing Black Box Exposed: 1.7 Million Overcharged, Anthropic Refunds But Doesn’t Admit Fault

A startup named Vaudit, founded by former Oracle director Michael Hahn, audits AI bills for companies and claims to have identified approximately $1.7 million in overcharges across 60 businesses, totaling $34 million in reviewed bills. The alleged discrepancies primarily involve charges for Anthropic's Claude Code. Common issues cited include billing for newer, more expensive models when older, cheaper ones were used; charging for failed or errored requests; and "retry storms" where AI agents silently retry failed tasks, accumulating costs unnoticed. Major clients like Panasonic, HP, and Honda were among those audited. While Vaudit reports that around 80% of the disputed charges were refunded by providers like Amazon, Google, Microsoft, Anthropic, and OpenAI after申诉, the AI companies largely deny systemic problems. Anthropic stated overcharges do not appear widespread and it does not bill for uncompleted requests or errors, while OpenAI said it found no evidence of such issues affecting its customers. The situation highlights the inherent opacity and complexity of AI billing, which is based on token usage that is difficult to track and predict, especially with multi-agent, multi-model workflows. This complexity is creating a new market for third-party AI bill auditing services like Vaudit, which charges fees based on recovered amounts. Separately, Anthropic faces a proposed class-action lawsuit alleging its high-tier subscription plans deliver far less usage than advertised. The case underscores growing scrutiny over AI service pricing and transparency as major providers prepare for IPOs.

marsbitHace 16 min(s)

AI Billing Black Box Exposed: 1.7 Million Overcharged, Anthropic Refunds But Doesn’t Admit Fault

marsbitHace 16 min(s)

Tencent Buys Baidu Chips

China's internet giants, once defined by building closed, self-sufficient empires, are undergoing a fundamental shift. A key signal is Baidu's plan to spin off its AI chip unit, Kunlun Xin, for a Hong Kong IPO targeting a $50 billion valuation, potentially exceeding its parent company's worth. Concurrently, Alibaba's T-Head is also pursuing independence. Most significantly, reports indicate that rival Tencent has become a major customer for Kunlun Xin's chips. This move, where competitors begin procuring each other's core technologies, marks a decisive break from the past era of internal duplication and isolation. It signals the maturation of China's AI industry into a more open, specialized ecosystem. The underlying driver is the immense and clear cost of AI infrastructure, particularly the exploding demand for inference compute driven by AI agents and applications. Hardware is no longer just an internal cost center but a profitable, strategic business in itself. Globally, a parallel trend is evident as OpenAI, Google, Amazon, and others develop their own AI chips to control costs and optimize performance. The competition has moved beyond model benchmarks to a deeper, foundational war over token cost efficiency, inference cluster performance, and secure, scalable computing power. Baidu and Alibaba aren't dismantling their empires but are instead decoupling non-core, capital-intensive infrastructure to participate in and shape a larger, collaborative industrial base. The era of the all-encompassing super-app is giving way to an age of strategic specialization and open ecosystem building in the AI race.

marsbitHace 32 min(s)

Tencent Buys Baidu Chips

marsbitHace 32 min(s)

The Token Itself Is an Asset: Three Types of Tokenized Stocks, Which One Suits You?

"Tokenized Stocks: Three Types, Which One Fits You? For investors outside the US, buying stocks like SpaceX or Nvidia is difficult, requiring brokers, cross-border transfers, and often accredited investor status. Blockchain offers an alternative through tokenized stocks, a term encompassing three distinct products with vastly different ownership, voting, and profit rights. 1. **Full Real Ownership**: Companies like Superstate register native equity directly on-chain (e.g., Solana). Holders are on the official shareholder registry, with full voting rights, dividends, and legal ownership. This offers maximum rights but potentially less DeFi flexibility. 2. **SPV-Backed Tokens (Surrendered Ownership for DeFi Composability)**: Issuers like Backed (xStocks) and Ondo use offshore Special Purpose Vehicles (SPVs) to hold underlying shares 1:1 and issue tracking tokens. Investors get price exposure and dividends (reinvested as more tokens) but hold a claim on the SPV, not direct stock ownership. This enables use as collateral in DeFi protocols (Kamino, Morpho) and 24/7 minting/redemption, but carries SPV counterparty risk (highlighted by the PreStocks collapse). 3. **Perpetual Futures (Pure Price Speculation)**: Platforms like TradeXYZ (on Hyperliquid) and Ostium offer perpetual contracts. These are synthetic derivatives with no underlying stock ownership, using funding rates to track spot prices. They require only a price oracle, allowing extremely fast listing (e.g., SpaceX pre-IPO) and high leverage, attracting speculators. Their trading volume far exceeds tokenized spot products. The core value of tokens is that they don't need to replicate full stock ownership. Most retail investors never vote. Tokenization creates layered financial tools: full equity for institutions, composable tokens for DeFi users, and perpetuals for leveraged traders."

marsbitHace 32 min(s)

The Token Itself Is an Asset: Three Types of Tokenized Stocks, Which One Suits You?

marsbitHace 32 min(s)

AI as the Boss: Nearly Bankrupts 10 Companies...

A recent study from Princeton University tested 14 AI models, including large language models (LLMs) and a rule-based algorithm, in a simulation where they acted as CEOs of a virtual SaaS startup over 500 days. The goal was to grow an initial $1 million capital. The results were stark: only four "CEOs" ended with a profit. The top performer was Claude Fable 5, multiplying the capital 47-fold to $47.15 million. Claude Opus 4.8 and GPT-5.5 followed. Notably, the fourth profitable entity was a simple, pre-programmed rule-based algorithm, which outperformed many advanced LLMs with $15.76 million in profit. Five other models, including several major LLMs, went bankrupt before the simulation ended. Key takeaways from the research highlight that successful AI CEOs demonstrated a tendency for exploration and adaptation over caution. They excelled in discovering hidden information, predicting future cash flow, adapting quickly to changes (like competitor moves), and engaging in strategic "if-then" planning. The study also found that equipping LLMs with programming-agent frameworks, optimized for coding tasks, actually harmed their performance in this CEO role, suggesting a need for domain-specific adaptations. The article concludes by contrasting AI's current operational proficiency within defined frameworks with the type of visionary, intuitive decision-making—exemplified by figures like Steve Jobs—that truly drives transformative business strategy. This critical "matrix-drawing" capability, it argues, remains uniquely human.

marsbitHace 42 min(s)

AI as the Boss: Nearly Bankrupts 10 Companies...

marsbitHace 42 min(s)

Trading

Spot
活动图片