SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Odaily星球日报Published on 2024-03-05Last updated on 2024-03-05

Abstract

数字货币方面，BTC 一度扩大涨幅至历史最高点附近后遭遇阻力回调 3% 左右，收报 66638.05 （+ 4% ）；ETH 上行势能不减，继续挑战近期新高，收报 3682.71 （+ 6.1% ）。

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

昨日（6 MAR）亚特兰大联储主席博斯蒂克在文章中表达了对过快降息可能会加剧价格压力的担忧，并在问答中进一步提到预计首次降息后将暂时按兵不动以评估其影响的看法。美国三大股指轻微收跌。美债方面，对利率政策较为敏感的两年期美债收益率上涨至 4.583% ，十年期下行现报 4.188% 。

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Source: SignalPlus, Economic Calendar

数字货币方面，BTC 一度扩大涨幅至历史最高点附近后遭遇阻力回调 3% 左右，收报 66638.05 （+ 4% ）；ETH 上行势能不减，继续挑战近期新高，收报 3682.71 （+ 6.1% ）。期权方面，两币种隐含波动率均在高位大幅震荡，BTC 70000-C 成为市场成交热点，市场的 FOMO 情绪推动短期（8 MAR/15 MAR）持续涌现买涨建仓， 29 MAR 则多为看空的卖单，整体买卖较为均衡，形成了日历组合。ETH 的成交集中体现在三月 4000-C 的买单，其稳步增长的行情为买涨交易提供了信心，且相比 BTC 来说，ETH 离他的历史最高点（4800）也还有不少的上行空间。

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Source: Binance & TradingView，BTC 在接近 ATH 的位置受到阻力

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Source: Deribit （截至 5 MAR 16: 00 UTC+ 8）

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Source: SignalPlus, ATM Vol 变化

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Data Source: Deribit，BTC 成交分布；70000-C 成为交易热点

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Data Source: Deribit，ETH 成交分布；三月份的 4000-C 被大量买入

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Source: Deribit Block Trade

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

Source: Deribit Block Trade

SignalPlus波动率专栏(20240305)：BTC在历史高点前遭遇回调，ETH稳步上行追赶

您可在 ChatGPT 4.0 的 Plugin Store 搜索 SignalPlus ，获取实时加密资讯。如果想即时收到我们的更新，欢迎关注我们的推特账号@SignalPlus_Web3 ，或者加入我们的微信群（添加小助手微信：SignalPlus 123）、Telegram 群以及 Discord 社群，和更多朋友一起交流互动。

SignalPlus Official Website：https://www.signalplus.com

Related Reads

Why Does 'AGI Godfather' Ben Goertzel Believe the Future of AI Relies on Blockchain?

Ben Goertzel, known as the "AGI Godfather," argues that the future of Artificial General Intelligence (AGI) must be built on blockchain to prevent its control by a few corporations or venture capital firms. He believes the core AGI code should be free and open-source, but that this alone is insufficient without a decentralized infrastructure to run it affordably. His blockchain project, SingularityNET, and the broader Artificial Superintelligence Alliance aim to create a user-owned, decentralized network for hosting and deploying AGI, contrasting with the closed models of companies like OpenAI and Anthropic. Goertzel criticizes the shift of other labs from open to closed development. He argues that while a closed path is simpler, an open, decentralized model—akin to Linux and the internet—is both possible and ultimately better for humanity. He envisions an "Agent economy" where individuals orchestrate teams of AI agents to perform tasks, including transactions, on an open network rather than corporate clouds. While his current model relies on cryptocurrency, plans include offering paid AI services to businesses with the decentralized blockchain as the backend. Goertzel predicts human-level AGI could arrive by 2029 and warns that a gap in understanding and access to AGI could drastically worsen inequality. The first test of his decentralized approach will be the upcoming release of the Agent Omega Claw.

Foresight News6m ago

Why Does 'AGI Godfather' Ben Goertzel Believe the Future of AI Relies on Blockchain?

Foresight News6m ago

A Company Once on the Verge of Collapse Now Has a Market Cap Surpassing Bitcoin

"Once nearly bankrupt, SK Hynix now surpasses Bitcoin in market cap." On June 22, SK Hynix's market value reached $1.35 trillion, exceeding Bitcoin's $1.29 trillion, driven by soaring demand for its High-Bandwidth Memory (HBM), a critical component for AI training. As NVIDIA's primary HBM supplier with over 60% market share, the company reported a 72% operating profit margin in Q1. Its remarkable turnaround stems from a 13-year bet on HBM technology, initiated in 2009 and rescued by SK Group's acquisition in 2012. The company plans a Nasdaq listing, potentially attracting more institutional capital. This milestone highlights a market preference for tangible AI infrastructure assets—like HBM with its physical scarcity and verifiable revenue—over narrative-driven crypto-AI projects, which remain in early developmental stages and lack comparable proof of scalable demand or economic models. The capital shift underscores the premium placed on real-world supply constraints and profitability in the current AI boom.

marsbit13m ago

A Company Once on the Verge of Collapse Now Has a Market Cap Surpassing Bitcoin

marsbit13m ago

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

On June 22nd, driven by rising stock prices, SK Hynix’s market capitalization reached $1.35 trillion, surpassing Bitcoin's total market cap of approximately $1.29 trillion. This temporarily made it South Korea's highest-valued company. The core driver of this surge is HBM (High Bandwidth Memory), for which SK Hynix is the primary supplier to NVIDIA, holding over 60% market share. AI's demand for high memory bandwidth has translated into immense profitability, with SK Hynix reporting a 72% operating profit margin in Q1. The company's success follows a 13-year bet on HBM technology, beginning in 2009. It nearly failed after the 2001 dot-com bubble, was acquired by SK Group in 2012, and was subsequently recapitalized to continue its long-term HBM development. The article contrasts this with the Crypto AI narrative. Capital currently favors AI infrastructure players like SK Hynix due to "real orders, physical barriers, and quantifiable profit margins." In comparison, Crypto AI projects, promising decentralized compute and data markets, remain largely conceptual with limited tangible progress. Examples include Bittensor, whose core mechanisms are still under development, and Bitcoin miners transitioning to AI, who face significant funding gaps and execution challenges. The piece cites analysis suggesting the AI sector has absorbed nearly all new market liquidity since 2022, leaving little for crypto. It concludes that the current AI infrastructure红利 is captured by entities with proven technical barriers and supply capabilities, while crypto networks still need to define their concrete role in the value chain.

链捕手46m ago

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

链捕手46m ago

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

Bittensor, a decentralized AI protocol, is accelerating its transition to full decentralization over the next 18 months, as outlined in a recent post by co-founder Const. The project currently operates in a "semi-decentralized" state: ownership and network participation are open and permissionless, with TAO distribution based on competitive contribution. However, protocol upgrades and governance have remained under core team control to enable rapid iteration in the fast-evolving AI sector. This strategic shift comes as the ecosystem matures, boasting 128 subnets and a large community. Const argues that continued centralization now poses risks, including single points of failure and regulatory scrutiny. The upcoming decentralization roadmap includes optimizing validator competition, opening liquidity pools, introducing governance rights for Alpha holders, and refining economic models. The move could fundamentally reshape TAO's value proposition, adding governance premiums to its existing valuation based on AI narrative and scarcity. It also signals a potential maturation of the AI crypto sector, where competition may shift from hype to sustainable protocol design and real economic activity. Bittensor positions itself not just as another AI token, but as foundational infrastructure aiming to decentralize intelligence production—analogous to Bitcoin's role in decentralizing money—with the goal of creating a resilient "Millennium Intelligence Federation."

marsbit59m ago

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

marsbit59m ago

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

In June 2026, Sakana AI's new model Fugu caused a stir in the AI community. Its Fugu Ultra variant achieved scores of 73.7 on SWE-Bench Pro and 82.1 on TerminalBench 2.1, surpassing GPT-5.5 and Claude Opus 4.8, and was claimed to be comparable to export-restricted models like Fable 5 and Mythos Preview. Remarkably, the core of this high-performance system is not a massive model, but a small 7B-parameter RL Conductor model. Fugu operates as a multi-agent orchestrator: the 7B model acts as a "foreman," dynamically analyzing user tasks and delegating subtasks to a pool of top-tier global models (e.g., GPT-5, Gemini 3.1 Pro). It then synthesizes and verifies their outputs. This architecture represents a paradigm shift from monolithic models to an expert-team approach. It enhances performance in complex, multi-step engineering tasks like code review and security testing by enabling cross-validation from specialized models, improving long-session stability and token efficiency. However, Fugu's strengths come with trade-offs: it faces inherent latency due to multiple API calls, relies heavily on underlying US model APIs (creating dependency risks), and its benchmark comparisons with Fable/Mythos are based on reported scores, not head-to-head testing. For Japan's AI ecosystem, which lacks the massive compute and data resources of the US or China, Fugu exemplifies an "asymmetric breakthrough" strategy. Instead of competing directly in parameter scale, it focuses on intelligent orchestration of existing global models, offering a degree of AI sovereignty and resilience. While a significant system-level innovation, its ultimate capability is still bounded by the underlying models it coordinates.

marsbit59m ago

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

marsbit59m ago

Trading

Spot
Futures
活动图片