Сумасшедший трейдер спрогнозировал рост курса Dogecoin до $4,2

cryptonews.ruОпубліковано о 2021-08-23Востаннє оновлено о 2025-01-23

Трейдер под псевдонимом Zer0, торгующий токенами-мемами, предсказал безумный 12-кратный рост курса криптовалюты Dogecoin (DOGE).

Zer0 проанализировал исторические данные и пришёл к выводу о том, что рынок Dogecoin преодолел лишь первую фазу бычьего ралли, когда монета стремительно подорожала от $0,1 до $0,48 с октября по декабрь 2024 года. После окончания этого периода, как и во время предыдущих циклов, возникла коррекция, в результате которой цена монеты рухнула на 46%. Затем произошёл отскок ото дна, и курс пошёл вверх.

Трейдер убеждён, что в скором времени цену Dogecoin снова будут пампить, и она достигнет $4,2 в ходе двух восходящих рывков, отделённых друг от друга краткосрочной коррекцией. Если прогноз торговца криптовалютами сбудется, то DOGE подорожает в 12 раз от текущего показателя и озолотит ходлеров, которые успеют продать токены на пике.

В этом случае курс криптовалюты вырастет в 42 раза с момента старта восходящей тенденции, и текущее бычье ралли уступит двум предыдущим, в рамках которых стоимость монеты повысилась в 92 и 300 раз соответственно.

zer0-doge-pump-graph

Прогноз на изменение курса Dogecoin на графике, составленном Zer0

Одним из катализаторов второго этапа бычьего ралли на рынке Dogecoin может оказаться выпуск ETF на базе этого цифрового актива. Создать деривативы на основе DOGE хотят три американские компании: Bitwise, Osprey Funds и REX Shares.

Как полагает сотрудник Bloomberg Эрик Балчунас, торговлю Dogecoin-ETF запустят в апреле 2025-го, конечно, если всё пройдёт гладко и Комиссия по ценным бумагам и биржам США согласует выпуск фондов. Поэтому нового витка восходящей тенденции на графике изменения курса Dogecoin стоит ожидать весной.

Пов'язані матеріали

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

This article explains the three primary methods for Codex to interact with a computer, each with distinct use cases, permission boundaries, and trust levels. **1. Computer Use:** This offers the broadest access, allowing Codex to visually control and interact with the graphical user interface of authorized macOS/Windows apps, system settings, and even iOS simulators. It's ideal for tasks lacking APIs or structured tools, such as operating legacy software or multi-app workflows. However, it's the slowest method and has the widest permission scope, requiring careful supervision for sensitive actions. **2. Chrome Extension:** This grants Codex access to the user's logged-in Chrome browser state, including cookies, profiles, and open tabs. It's best for tasks requiring user identity across websites like Gmail, LinkedIn, Salesforce, or internal dashboards. Its key advantage is multi-tab control for complex workflows. While more powerful for browser-based tasks than Computer Use, it carries higher sensitivity as actions are performed under the user's identity. **3. In-App Browser:** This is a browser isolated within the Codex thread, separate from the user's personal browsing data. It excels in web development and debugging scenarios—previewing local servers, testing responsive layouts, or annotating designs directly on the page. Its isolation is a strength for development but a limitation for tasks requiring login sessions. The core principle is to choose the narrowest, safest, and most structured interface for the task. Use plugins or MCPs first, resort to visual control (Computer Use) only for GUI-dependent tasks, employ the Chrome extension for identity-reliant browser work, and prefer the In-App Browser for isolated development. **Appshots** are clarified as a fourth, complementary tool for *inputting* context—capturing a screenshot of a window to point Codex to something—rather than a method for Codex to *act*. Together, this layered approach highlights a key to AI agent productization: not granting unlimited permissions, but constraining them within clear boundaries for specific tasks while preserving user oversight.

marsbit1 год тому

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

marsbit1 год тому

The "Iron Rule" of Chip Equipment Is Being Broken

For years, the semiconductor equipment industry followed an unwritten "iron rule": suppliers offered steep discounts for new tool introductions (Design-in) and faced consistent price pressure during repeat orders, especially during market downturns. This long-standing buyer's market dynamic is now being upended. Recently, SK Hynix's primary equipment suppliers have reportedly requested a 3-4% price *increase*, a nearly unprecedented move. This shift is driven by a severe supply-demand imbalance fueled by the AI compute boom. Securing equipment has become an urgent arms race as chipmakers' expansion speed dictates their ability to fulfill massive AI chip orders. Key areas feeling the strain include: **TCB (Thermal Compression Bonding) Equipment:** Demand is exploding, driven by the simultaneous needs of HBM4 memory stacking, AI chip Chip-on-Substrate (C2S), and logic Chiplet Chip-on-Wafer (C2W) packaging. Players like Hanmi Semiconductor, Hanwha Semitech, and ASMPT are receiving major orders. While hybrid bonding is seen as the future, TCB remains the pragmatic choice for HBM4 mass production, with its lifecycle extended by relaxed specifications and ongoing technological upgrades. **Test Equipment Bottlenecks:** Ironically, AI-driven shortages are now crippling test equipment manufacturing. Critical components like FPGAs, Driver ICs, and CPUs face severe shortages and extended lead times (up to 52 weeks for FPGAs), as AI data center and server vendors prioritize supply. This creates a paradoxical cycle: AI chip shortages drive fab expansion, which requires more test equipment, whose production is delayed because its key parts are diverted to make AI chips. The industry is entering a broad, AI-powered upcycle. SEMI forecasts global semiconductor equipment sales to hit a record $156 billion by 2027, fueled by investment in advanced logic/foundry, HBM-driven DRAM, and advanced packaging (like CoWoS). Major players like TSMC, SK Hynix, and Micron are aggressively ramping capital expenditure. In conclusion, leading equipment vendors are no longer just selling tools; they are selling the critical capability to deliver AI-era capacity. Pricing power is shifting decisively to those with indispensable technology in key process nodes like advanced logic, HBM, and advanced packaging, rewriting the industry's traditional power structure.

marsbit1 год тому

The "Iron Rule" of Chip Equipment Is Being Broken

marsbit1 год тому

Торгівля

Спот
Ф'ючерси
活动图片