火星早报 | 特朗普对等关税生效时间延迟一周至 8 月 7 日

marsbit2025-07-31 tarihinde yayınlandı2025-08-01 tarihinde güncellendi

CoinbaseCoinbase发布 Q2 财报:净利润达 14.3 亿美元远超去年同期,但交易收入环比下降 39%

据 Coinbase 最新季度财报披露,此前曝光的用户数据泄露事件最终造成 3.07 亿美元损失。Q2 整体表现如下: · 净利润达 14.3 亿美元,远超去年同期的 3600 万美元 · 总交易量 2370 亿美元,较 2024 年同期 2260 亿美元略有增长 · 环比一季度,交易收入下降 39%,现货交易量减少超 30%。

Mill City Ventures 成功完成 4.5 亿美元私募并启动 SUI 财库策略

据 BusinessWire 报道,Mill City Ventures III, Ltd.(纳斯达克代码:MCVT)宣布成功完成 4.5 亿美元私募股权融资,并正式启动其首创的 Sui 区块链财库管理策略。此次融资由伦敦数字资产对冲基金 Karatage Opportunities 牵头,Sui 基金会等机构等额参与。 Karatage 联合创始人 Marius Barnett 和 Stephen Mackintosh 分别出任董事会主席和首席投资官。Mill City 现持有 76,271,187 枚 SUI 代币,平均购入价为每枚 3.6389 美元,成为唯一获得 Sui 基金会官方支持的上市公司 SUI 国库。

Pump.fun于近期注册子域名fee.pump.fun

8 月 1 日,据市场消息,Pump.fun 于近期注册了 fee.pump.fun 子域名,预示即将推出费用仪表板或基于交易量的激励计划。

合约巨鲸AguilaTrades的40倍BTC多单再次遭到清算,整体已亏损3980万美元

8 月 1 日,据 Onchain lens 监测,合约巨鲸 AguilaTrades 的 BTC(40 倍)多头仓位再次被部分清算,迄今为止在此次交易中已损失 278 万美元。 AguilaTrades 目前整体亏损 3980 万美元。他总共向 HyperLiquid 账户存入了 4005 万美元的 USDC,目前仅剩 20 万美元。

Strategy 第二季度净利润达 100 亿美元,拟筹资 42 亿美元增持比特币

据 Strategy 官方公告,其公司在 2025 财年第二季度实现营业收入 140.3 亿美元,净利润 100.2 亿美元,每股摊薄收益 32.60 美元。截至 7 月 29 日,公司比特币持仓量已增至 628,791 枚,总成本达 460.7 亿美元,平均每枚比特币成本为 73,277 美元。公司 2025 年迄今已实现 25% 的比特币收益率和 132 亿美元的比特币收益。此外,Strategy 宣布将通过发行 STRC 永续优先股筹资 42 亿美元用于继续增持比特币。

证券时报:中行、渣打等发钞行有望率先获批香港稳定币牌照

据金十数据援引证券时报报道,香港《稳定币条例》正式生效,香港金融管理局已发布《持牌稳定币发行人监管指引》,明确了发行人牌照申请的各项门槛。证券时报获悉,中国银行(香港)、渣打银行(香港)等发钞行有望率先申请并获批稳定币发行人牌照。此外,中资银行、沙盒测试企业、大型央国企和互联网大厂也积极筹备申请。券商初期将主要提供稳定币交易、托管、融资等服务。 截至 7 月末,已有 44 家金融机构升级了第 1 号证券交易牌照。业内人士提醒,稳定币商业模式尚不明朗,投资者需警惕概念炒作及风险。

特朗普对等关税生效时间延迟一周至 8 月 7 日

当地时间周四晚上,美国总统特朗普签署行政命令,对从 67 个贸易伙伴出口至美国的商品征收 15% 至 41% 不等的关税,将关税水平提高到一个多世纪以来的最高水平。 然而,新关税要到 8 月 7 日才会生效,而不是之前的 8 月 1 日,这给了各国另一个试图通过谈判降低关税的窗口。一名高级政府官员说,“这是历史性的,这是一个新的贸易体系,这就是我所说的特朗普回合谈判。”白宫官员周四晚间表示,他们希望在新的关税实施日期 8 月 7 日之前,与各国达成更多协议。

0xSun:已做多ETH并做空一揽子山寨币进行对冲,认为机构买入ETH的资金不会溢出到其他山寨

8 月 1 日,Smart Money、加密 KOL 0xsun.sol(@0xSunNFT)在社交媒体上发文表示,目前市场多空分歧严重,个人目前已开设一笔对冲交易(做多 ETH&做空一揽子山寨),仓位大概为 1:1。 做多 ETH 的逻辑是,ETH 是六月末这轮上涨的主要推动力,机构效仿微策略,通过币股融资购买 ETH。而在稳定币叙事中,ETH 也是相关的核心基建与结算层。参考此前微策略购买 BTC,推动价格一路上涨的过程,最终大部分山寨涨幅远不及比特币。币股和机构用于买入 ETH 的这部分资金,也不太会外溢到其他山寨上。 另据 CMC 数据显示,过去 30 天 Top200 的代币里涨幅大于 ETH 的只有 20 个,包括 BONK、ZORA、CFX、ENA 这些明显受利好事件驱动的。 山寨币遵循此前做空的逻辑,优先选择市值偏高、非龙头、走法不强势、存在感低的,并且分散做空,设好止损,防止单个标的爆拉。 0xsun 补充表示,若下半年后市继续走牛,相信很大概率依然是会由 ETH 推动。若行情进入熊市,也不觉得山寨可以独善其身,而 ETH 至少有机构的购买力托底。会导致这个对冲思路失效的情况,要么是山寨季真的来了,大部分山寨都持续跑赢 ETH,要么是 ETH 震荡或者领跌,而其他山寨反而跌的不多,按照这几个月的经验,个人觉得可能性较小。

Bitunix分析师:美6月PCE通胀回升+加税风险升温,BTC测试压力三角末端,短期支撑守稳117,000

8 月 1 日,美国 6 月核心 PCE 年率录得 2.8%,高于预期与前值修正值,为 2 月以来最快通胀增速。同时整体 PCE 与消费支出同步攀升,凸显通胀压力重现,而劳动市场疲弱与实际收入停滞则强化经济放缓风险。市场预期本周五就业报告将进一步证实招聘动能下滑,增添政策路径不确定性。 BTC 方面,日线图显示价格自高位盘整后逐步收敛,当前测试下降趋势线与横向支撑的三角形末端,118,500–118,800 区域为短期压力,116,300 则为强支撑。清算热力图同步显示,下方 117,000 聚集大量清算买盘,支撑结构尚稳,但上方 120,000 卖压未见减弱。 Bitunix 分析师建议: 6 月 PCE 反弹增添通胀不确定性,叠加市场等待特朗普新关税政策,整体风险偏空。BTC 盘面处于收敛三角末端,短线或面临方向选择,建议暂不追价,观察是否有效突破 118,800 或跌破 116,300 再做布局。

Base提的「内容代币基本面」,为什么让Solana反应这么大?

2025年2月,Base生态社交平台Zora推出「COIN」功能,引发关于「内容币」价值的争论。Base创始人Jesse Pollak认为内容币具备基本面价值,而Solana联创Anatoly Yakovenko则批评其依赖投机。双方争论的核心在于内容代币是否具有长期价值,还是仅属短期炒作。目前Zora生态虽增长迅速,但用户规模仍远未达到支撑「基本面」所需的体量,多数内容币仍呈现高波动性。这场辩论反映了加密行业对价值捕获方式的根本分歧。

70倍神盘崩了,meme的DeFi IMF还能回来吗?

以太坊MemeFi项目$IMF在6月至7月间暴涨70倍后,因大规模抛售引发85%暴跌,导致连环清算和1%坏账。IMF平台允许用户抵押meme币借贷稳定币,但开放$IMF自身代币抵押引发套现质疑。尽管官方否认协议问题并澄清坏账可控,争议仍持续,市值从最低点反弹3倍至2100万美元。项目被指利用短期买盘操纵市场,团队反驳称上架标准透明。

Mento的野望:从稳定币到全球外汇基建,一场迟来的链上金融革命

Celo生态稳定币平台Mento正转型布局万亿美元链上外汇市场,通过跨链协议Wormhole将其15种法币稳定币扩展至Solana等公链,并构建多币种DEX。其200%超额抵押机制虽保障安全性,却抑制了非主流币种的流动性。面对亚洲市场需求与监管挑战,Mento试图从支付工具升级为全球链上外汇基础设施,但需解决资本效率与用户体验等关键问题。

İlgili Okumalar

Near Returns to the AI Stage: Transformation into a Public Chain Due to 'Payroll Difficulties,' Agent and Privacy Emerge as New Growth Narratives

NEAR Returns to AI Origins: From Payroll Struggles to Blockchain, Now Focusing on AI Agents and Privacy NEAR Protocol's journey began not with grand blockchain ambitions, but from a practical hurdle: its AI startup founders, including Transformer paper co-author Illia Polosukhin, couldn't efficiently pay international developers in 2017. This led them to pivot and build a high-performance, scalable blockchain. After years navigating various crypto narratives like sharding and cross-chain interoperability, NEAR is now leveraging its AI roots to re-enter the AI arena. A key driver is its "NEAR Intents" layer, which abstracts complex cross-chain transactions. Users simply state their goal (e.g., swap BTC for ETH), and a solver network finds the optimal route. This system has processed over $20B in cross-chain volume, generating significant fee revenue. A major growth area is private transactions via "Confidential Intents/Swaps," which hide trade details until settlement to protect against MEV and front-running. Remarkably, private swaps recently accounted for over 40% of NEAR's transaction volume, highlighting strong demand but also potential regulatory scrutiny. With its AI-founder pedigree, NEAR is positioning itself at the intersection of blockchain, AI agents, and privacy, aiming to become infrastructure for the emerging agent economy while navigating the challenges of its rapid adoption.

marsbit1 saat önce

Near Returns to the AI Stage: Transformation into a Public Chain Due to 'Payroll Difficulties,' Agent and Privacy Emerge as New Growth Narratives

marsbit1 saat önce

From Ethereum to AI's 'CROPS': What Exactly is This Set of 'Slow Variables' That Vitalik Repeatedly Emphasizes?

In recent discussions, Vitalik Buterin has frequently emphasized the concept of "CROPS," a framework defining core values for Ethereum's development. CROPS stands for Censorship Resistance, Capture Resistance, Open Source, Privacy, and Security. Initially outlined in the Ethereum Foundation's "EF Mandate," it represents a commitment to user sovereignty, ensuring that the network resists external control, remains open, protects privacy, and prioritizes security. The relevance of CROPS extends beyond Ethereum's foundational principles, becoming crucial in the context of AI integration. As AI agents begin handling wallet operations and automated transactions, the risk increases that users may cede control over their digital assets, privacy, and intentions to centralized AI service providers. A "CROPS AI" would therefore emphasize local execution where possible, privacy-preserving remote model calls (e.g., using zero-knowledge proofs), and transparent, verifiable processes to maintain user agency. Vitalik highlights a significant convergence between "CROPS Ethereum access layer" and "CROPS AI." Both address the same fundamental challenge: how users can access powerful services—be it blockchain data via RPCs or AI models—without exposing sensitive information or relinquishing ultimate control. This intersection points toward a future digital entry point that is more private, secure, and user-controlled. Ultimately, CROPS is not merely an abstract ideal but a practical guidepost. It steers development—from protocol resilience and wallet design to AI agent safety—towards a future where users retain self-sovereignty even as digital systems grow more complex and powerful. In an era of accelerating AI adoption, these "slow variables" of censorship resistance, openness, privacy, and security may define Ethereum's enduring value.

marsbit2 saat önce

From Ethereum to AI's 'CROPS': What Exactly is This Set of 'Slow Variables' That Vitalik Repeatedly Emphasizes?

marsbit2 saat önce

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit3 saat önce

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit3 saat önce

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit3 saat önce

Token Inefficient, Economy Tokenless

marsbit3 saat önce

İşlemler

Spot
Futures
活动图片