ETH虽说短期被质疑、长线来说依然看好、可以择机抄底

币界网Published on 2024-08-21Last updated on 2024-08-21

币界网报道:

空头观点

  • 在 Dencun 之后,盈利能力急剧下降,这种情况短期内看起来不会改变。

  • ETH 的市场契合度正在减弱。加密货币纯粹主义者希望拥有 BTC,普通投资者则被 $SOL 吸引,而 $TRX 正在捕获稳定币的转移。“一刀切”的方法不再适用。

  • L2 正在变得越来越分散。目前,正在跟踪 71 个 L2、20 个 L3,以及令人惊叹的 82 个即将推出的项目。这大大降低了用户体验,并成为广泛采用的重要障碍。与此同时,SOL 展现了单体链和生态系统的潜力。

  • DeFi 的实用性正受到质疑。许多项目本质上只是带有掠夺性代币经济学的梗。高流通量、低完全稀释市值的模式旨在从普通投资者那里提取尽可能多的价值,转移到风险投资者的口袋中。

  • ETH ETF 的表现乏善可陈。

OrwO5n4dfLu1q05JyALsM4BlpfQS5d3WrWd5MBlV.jpeg

以太坊 ETF 的影响分析

比特币 ETF 为许多新买家打开了在其投资组合中配置比特币的机会。而 ETH ETF 的影响则不那么明确。

  • ETH 的市场情绪处于历史低点。结合 ETHBTC 和 SOLETH 交易对的低迷表现,我们可能会看到死亡螺旋和链上总锁仓价值 (TVL) 的外流。

  • 我们已经被条件反射地认为 ETH 是“被选中的” L1,但在如此新兴的行业中,这种观点并不一定成立。

  • 从机构和政治的角度来看,BTC 是主要焦点。像迈克尔·塞勒这样的纯粹主义者正在倡导 BTC 作为最坚硬的货币形式,而这种叙述在 ETH 中并不存在。ETH 正在努力寻找类似的“支持者”。

多头论点

  • ETH 和 L2 的交易量达到了历史新高,而交易价格则接近低点。以太坊成功地进行了扩展,已经准备好迎接大众的到来。

cUYoJwqYWFgXS7J4XlHO7SGWdb9pfuxOtFx1Z0uD.jpeg

  • ETH 的总锁仓价值 (TVL) 是其最近竞争对手的 10 倍(不包括 L2)。L2 的 TVL 仍然锁定在以太坊生态系统中,这部分价值最终应该会归属于 ETH 持有者。

  • ETH 依然是主要的机构级链,经过多年的考验,开发者活动也处于最高水平。许多在这个领域最聪明的头脑正在共同制定 ETH 的发展路线图。任何机构的接入都会在 ETH 上进行,无论是现实资产 (RWAs) 的链上代币化、预测市场等。

  • ETH 今年的表现不佳与从 DeFi 转向 meme 的趋势相吻合。然而,叙述似乎正在发生变化。

DeFi 真的回来了?

在被其他叙述边缘化之后,DeFi 复苏的迹象正在显现。

  • ETH 今年继续找到杀手级应用,这种情况只会继续,等到下一个“DeFi”显现时,价格已经反映了现实——市场是前瞻性的。

  • 正在开发的多种互操作性解决方案——在几年内,我们可能几乎不需要知道我们连接的是哪个链。

  • ETH ETF 的推出是在与比特币完全不同的市场环境中进行的,且遭遇了糟糕的价格表现,这让潜在投资者感到失望。目前,政治和机构的关注主要集中在 $BTC 上,但随着比特币被越来越多的人接受,大家会开始问:“接下来是什么?” $ETH 无疑是这个问题的显而易见的答案。

  • 在历史低点(ATL)时的市场情绪为投资者创造了机会——价格的波动推动了市场叙述。随着投机者开始抄底,以上所有因素都逐渐明朗,导致价格向上反弹。

结论

多空双方都有如此强有力的论据,这可能会导致价格在任一方向上产生较大的波动。尽管作为 ETH 持有者我有一定的偏见,但我认为从长远来看,多头论点更加引人注目,特别是在经历了今年的价格波动之后。

Trending Cryptos

Related Reads

Deforming the Transformer, LLMs Become Smarter

A new research paper proposes "Tapered Language Models (TLMs)," a method that improves large language model performance without adding any parameters. It challenges the standard Transformer design where each layer has the same number of parameters ("feed-forward network" width). Building on evidence that layers are not equally important—earlier layers handle foundational information like grammar, while later layers often reinforce existing judgments—the researchers suggest reallocating model capacity from later to earlier layers. The core idea is to make the layer width taper off monotonically from start to end, keeping total parameters and compute constant. Experiments compared linear, cosine, and sigmoid tapering curves on a 440M parameter model. The cosine curve (e.g., starting width 1.5x baseline, ending 0.5x) achieved the best result, reducing perplexity by 1.84 points compared to the uniform baseline—a significant gain at zero cost. This finding proved robust across four different model architectures (including gated attention and memory-augmented models) and at larger scales (760M and 1.3B parameters), consistently improving performance on commonsense reasoning and language modeling tasks without harming long-context retrieval ability. The work highlights a long-overlooked design dimension: optimal parameter allocation across depth. It offers a "free lever" for efficiency, potentially applicable beyond language models to vision Transformers and diffusion models. The study was conducted by researchers from Mila, Cornell University, and the University of Montreal.

marsbit4m ago

Deforming the Transformer, LLMs Become Smarter

marsbit4m ago

From SpaceX to Galaxy Digital: A Detailed Look at 37 New AI Companies and 7 Crypto Dark Horses Added to the Russell Indexes

On June 26th, following its annual reconstitution, the Russell US Indexes finalized their new components, with changes taking effect for market trading on June 29th. The Russell 3000 Index, representing approximately 98% of the investable US equity market, saw significant turnover. A record $334 billion was traded during Nasdaq's closing cross on reconstitution day, highlighting the massive passive fund flows tied to these benchmarks. Companies newly added to the index are set to benefit from mandatory buying by these funds. The reconstitution raised the market cap threshold between the large-cap Russell 1000 and small-cap Russell 2000 by 24% to $5.7 billion. Overall, 224 new companies entered the Russell 3000. Of these, 19 joined the Russell 1000, and 205 joined the Russell 2000, while 118 firms were removed. Notably, among the newcomers, approximately 37 are companies operating in the AI and semiconductor ecosystem, accounting for roughly 17% of new additions. The most prominent is SpaceX, which, following its recent IPO and soaring valuation, was fast-tracked directly into the Russell 1000 and Top 200 indexes. Additionally, about 7 cryptocurrency-related companies were newly included, representing about 3% of new entrants. These include Galaxy Digital, Bitmine, and Tron, among others. The inclusion of several Decentralized Autonomous Trust (DAT) entities signals the model's sustained market presence. For these smaller AI and crypto firms, index inclusion boosts visibility, potentially attracting further institutional investment and supporting their stock performance.

Odaily星球日报8m ago

From SpaceX to Galaxy Digital: A Detailed Look at 37 New AI Companies and 7 Crypto Dark Horses Added to the Russell Indexes

Odaily星球日报8m ago

Token Uneconomical

"Token Inefficiency" explores the rising economic burden of AI model token usage in enterprises, where escalating costs often fail to match tangible productivity gains. Major companies like Microsoft, Uber, and Meta are facing "token inefficiency"—characterized by budget overruns for tools like Claude Code with unclear returns. This inefficiency stems from supply-side factors like strategic model price hikes by leaders (e.g., Anthropic) and price increases in budget-friendly models, alongside technical waste in Agent systems through context traps, tokenizer inflation, redundant skill calls, and multi-Agent coordination overhead. A deeper demand-side challenge limits token value: their primary utility remains confined to highly digitalized domains like programming, which benefits from automatic, low-cost feedback loops. Extending tokens to physical world tasks or less digitalized industries faces the "Sim-to-Real Gap," where real-world validation is costly and slow, unlike in code compilation. The article warns that this inefficiency concentrates financial risk in mid-tier model developers, potentially fueling circular financing schemes and shadow credit bubbles. It also highlights societal externalities, as data center expansion strains local power grids and inflates utility costs for residents. To achieve a positive net token economy, the path forward requires dual efforts: technical optimizations (context compression, skill reduction, model routing, budget constraints) and business-side discipline (governance, cost attribution, ROI focus). The ultimate goal is shifting from showcasing AI capabilities to maximizing value per token, finding scalable commercial applications that justify the investment and bridge the digital-physical divide.

marsbit26m ago

Token Uneconomical

marsbit26m ago

Stock Price Halved in 45 Days, Is Circle Actually the "DeFi Barometer"?

Over a 45-day period, Circle's stock price plummeted by approximately 50% to around $63, coinciding with a significant $70 billion decline in the circulation of its USDC stablecoin from its peak. In contrast, Tether's USDT saw a much smaller reduction. Analyst Ed Engel posits that Circle acts as a barometer for DeFi activity, as a high correlation exists between USDC supply and ETH price movements. The vast majority of USDC is concentrated within crypto exchanges and DeFi protocols for yield generation, rather than for widespread daily use in payments or commerce, unlike USDT which has stronger real-world adoption in various regions. The recent contraction in DeFi Total Value Locked (TVL), following security incidents like the Kelp DAO attack, appears to mirror Circle's declining stock performance. While Circle is actively promoting USDC's use as a settlement asset on platforms like Hyperliquid and in institutional payment corridors—where its organic transfer volume surpasses USDT's—these efforts have not sufficiently driven growth in USDC's overall supply. The company's revenue remains heavily tied to DeFi's expansion. For Circle's investment narrative to change, it must either significantly reduce its reliance on the volatile DeFi sector or demonstrably prove that real-world adoption can substantially and sustainably increase USDC circulation. In the near term, market confidence hinges on DeFi addressing its inherent risk-reward imbalances.

marsbit59m ago

Stock Price Halved in 45 Days, Is Circle Actually the "DeFi Barometer"?

marsbit59m ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETH (ETH) are presented below.

活动图片