特朗普的加密马戏团：当华尔街之狼遇上区块链过山车

marsbitPublished on 2025-06-23Last updated on 2025-06-24

如同 4 月初一般，特朗普再次挥动着自己的“市场魔法棒”，上演了一出“强势行动激化矛盾，快速妥协放出利好”的拿手好戏，加密市场也随之经历了一场过山车式的行情变动。多头空头你方唱罢我登场，一时间加密市场热闹非凡。Odaily星球日报将于本文汇总近期的多空两大联盟的代表性巨鲸/机构，供读者参考。

多军占据上风，空头惨遭挨打：ETH 多头卷土重来，空军头子利润大幅回撤

在经历了此前伊以冲突等地缘政治带动的行情下跌之后，不少多头押注市场将强势反弹，而随着伊以在特朗普的调停下达成停火协议，市场果然如期反弹，由此，多军开始重新占据市场上风。

最惨倒霉蛋：ETH 多军出手，但做空 BTC 损失遭重

6 月 23 日，某鲸鱼向 Hyperliquid 存入 428 万枚 USDC，并开设了一个名义价值 1.01 亿美元的以太坊多头仓位，杠杆倍数为 25 倍，清算价 2196 美元。彼时，随着 ETH 的价格反弹，其累计浮盈一度高达 106 万美元。

鲸鱼开单信息

随后，该鲸鱼选择在 ETH 价格 2255 美元时挂上限价单，最终成功获利 136 万美元，剔除 8.7 万美元的手续费后，净盈利为 127 万美元。

但令人意想不到的是，该鲸鱼转而开仓以 40 倍杠杆做空 BTC，并最终在“特朗普利好”刺激下不得不频频平仓止损。目前，该地址 40 倍 BTC 空单浮亏约 97 万美元，而其整体亏损则增加至约 356 万美元，堪称“最惨交易员”。

地址：0x916Ea2A9f3ba1DDD006C52Babd0216E2AC54eD32

ETH 聪明钱： 10 倍做空 ETH，利润回撤 500 万美元

如果你要玩 ETH 合约，那么这个地址毫无疑问是必须关注的指标之一。正如我们此前在《空军牛市来了？地缘冲突下的加密投资操作大赏》一文中提到的那样，该地址过去 2 个月内多次踩中 ETH 低点与顶点，曾一个月内狂赚 2000 万美元。

目前，该地址仍持有 10 倍杠杆做空 ETH 订单，持仓高达 40000 枚 ETH，名义价值高达 9600 万美元左右，而其浮盈也从此前的 2000 多万美元回撤至 1560 万美元左右。

地址：0xcB92C5988b1D4f145a7B481690051F03EaD23a13

58 种代币做空头子：利润回撤 400 万美元

此前在 Hyperliquid 上开空 58 个币种（包括 BTC、ETH、SOL、XRP、PEPE、FARTCOIN、DOGE、AAVE、HYPE 等）的某巨鲸/机构浮盈从此前的 2134 万美元回撤至现在的 1617 万美元， 58 个空单中的浮亏仓位也从此前的 2 个增加到目前的 5 个，其中：

HYPE 空单累计浮亏 470 万美元；
MKR 空单浮亏 2 万美元；
WIF 空单浮亏 1.5 万美元；
AAVE 空单浮亏 5.6 万美元；
Neiro 空单浮亏 1800 美元。

地址：0x45d26f28196d226497130c4bac709d808fed4029

传奇交易员 AguilaTrades：多次开单成市场反指， 30 天内亏损 3400 万美元

此前，交易员 AguilaTrades 于 6 月 20 日 19: 30 将其 BTC 多单仓位加仓至逾 4 亿美元，当时 BTC 价格约为 106000 美元。此后，BTC 价格一路下行，最低触及 102340 美元，AguilaTrades 也因此第三次在大额加仓后遭遇回撤。

颇为传奇的是，AguilaTrades 堪称“小 James Wynn”，此前曾频频开单，多空都做，一度浮盈超 300 万美元，但最终，其高频交易还是难敌震荡多变的加密市场，据 Hypurrscan 数据，其 30 日内亏损高达 3400 万美元左右。

最新数据显示，其最近一笔多单平仓发生于下午 4 点 11 分，为盈利状态， 24 小时累计盈利约 100 万美元。

地址：0x1f250Df59A777d61Cb8bd043c12970F3AFE4F925

16 个代币做空头子：利润回撤近 400 万美元

此前在 Hyperliquid 上做空 16 个山寨币的“空军头子”也迎来了自己的“阶段性滑铁卢”——

其浮盈从此前的 968 万美元大幅回撤至 572 万美元， 24 小时累计浮亏约 248 万美元；

尽管如此，目前，其 16 个持仓中仍有 15 个为浮盈状态，仅 HYPE 的 3 倍空单浮亏约 205 万美元。

地址：0xa312114b5795dff9b8db50474dd57701aa78ad1e

多空转换的“漏网之鱼”：及时平空止盈，再度开启多单

据链上分析师余烬监测，某鲸鱼在凌晨 1 点反弹前最低点处获利平仓 BTC 及 ETH 空单，然后反手买入了 ETH 现货。

彼时，其持有价值 6280 万美元的空单：BTC 平仓价在 101, 400 美元左右，ETH 平在 2, 224 美元左右，累计盈利 307 万美元。

值得一提的是，该鲸鱼于下午 3 点 35 分再次开仓 20 倍杠杆做多 ETH，持仓 5000 枚 ETH，名义价值 1200 万美元，目前小幅盈利。

地址：0x348bb306e6887d244450cbb9fd608e7f8d0a40b4

BTC 做空巨鲸：平空获利 169.5 万美元，持有 40 倍 BTC 空单

据链上分析师 Ai 姨监测，自 2025 年 3 月以来多次做空 BTC 的一位巨鲸于今日凌晨 00: 00 至 01: 00 期间（几乎为反弹起点）平仓 314 枚 BTC 空单，获利 169.5 万美元。近一个月内，该巨鲸累计盈利已达 1004.8 万美元。

目前，该巨鲸仍持有价值 5400 万美元的 BTC 40 倍杠杆空单，浮盈约 100 万美元。

地址：0x5D2F4460Ac3514AdA79f5D9838916E508Ab39Bb7

ETH 快枪手：凌晨买入 1388 万美元的 ETH

据链上分析师 Ai 姨监测，一巨鲸于今天凌晨在 ETH 价格快速反弹期间，以均价 2299 美元买入 6037.24 枚 ETH，成交金额约为 1388 万美元。

目前，ETH 价格反弹至 2421 美元，按照改价格计算，该地址已浮盈约 73 万美元。但该地址已将 ETH 转出至地址 0x7C2c5e739dc8351D718C8719Eb8E20D325B2Ff01，随后部分资金存入 AAVE。

地址：0x349d6bfb2E0577233359e3734B1d67ef5B37c9d4

Bitcoin at 59,000 Is Not the Bottom, One Last Drop Needed! Chain Data and Liquidity Analysis: Where is BTC's True Bottom?

Based on analysis by trader Mr. Beggar, Bitcoin's (BTC) recent low of $59k is likely not the final cycle bottom. He argues that while a bottom is near, a final downward movement is still probable to target liquidity below that level, making a deeper low healthier for a sustainable reversal. Mr. Beggar's framework combines on-chain data for long-term cycles and liquidity-based technical analysis for shorter-term trades. His "four deep bear buying models" include Cointime Price (market cost weighted by coin holding time) and AVIV (an enhanced MVRV indicator), which currently suggest prices are nearing cyclical bottom zones. While a PSIP (Percent Supply in Profit) signal has flashed below 50%, it alone is not considered definitive; typically, the first signal is not the final bottom. He presents three potential scenarios for the current market: 1) a direct drop from here, 2) an upward liquidity sweep (stop hunt) of the recent high near $67.3k before declining, and 3) a direct reversal without new lows. He heavily discounts the third scenario due to significant un-swept liquidity in the $59k-$62.3k range, suggesting the market must revisit these levels. Mr. Beggar shares that he used on-chain signals to identify potential cycle tops in late 2024/early 2025 and later established low-leverage BTC-denominated short positions. He emphasizes the importance of risk management and staying within one's expertise ("strike zone"), warning against investing in assets like AI/semiconductor stocks simply because they are rising.

marsbit25m ago

Bitcoin at 59,000 Is Not the Bottom, One Last Drop Needed! Chain Data and Liquidity Analysis: Where is BTC's True Bottom?

marsbit25m ago

From Signal Monitoring to Strategy Copy Trading: How PPP Lowers the Barrier to Trading on Polymarket?

From Signal Monitoring to Strategy Copy Trading: How PPP Lowers the Barrier to Polymarket Trading The surge in trading demand on prediction markets like Polymarket, especially during events like the World Cup, exposes a common challenge for novice users: emotional and impulsive trading due to a lack of stable strategies and reliable signals. Prediction Position Platform (PPP) addresses this by serving as a Telegram-based tool for strategy discovery and automated copy-trading on Polymarket. PPP offers a suite of features through a subscription model. Key functionalities include 24/7 market signal monitoring (tracking smart money movements and rapid probability shifts), an "AI Address Analysis" tool to evaluate trader performance metrics, and specialized sections like a "World Cup Zone" for quick access to related markets. Its core value lies in two curated lists: the "Strategy Square," which identifies addresses suitable for long-term tracking based on comprehensive metrics like returns, win rate, and drawdowns, and the "Trading Leaderboard," highlighting recently outperforming addresses for short-term opportunities. Users can manually analyze any address or set up automated copy-trading with customizable parameters like investment amount and stop-loss. After initiating copy-trades, users can manage all positions from a unified dashboard, adjusting parameters or stopping follows as needed, and review historical performance data. Crucially, PPP employs a non-custodial wallet model, meaning user funds remain in their own self-custodied wallets, enhancing security and trust. In summary, PPP aims to reduce the learning curve and trial-and-error cost for Polymarket users by aggregating signals, curating and analyzing profitable traders, and facilitating automated, yet manageable, copy-trading execution.

Odaily星球日报26m ago

From Signal Monitoring to Strategy Copy Trading: How PPP Lowers the Barrier to Trading on Polymarket?

Odaily星球日报26m ago

Post-95s Doctoral Graduate Ventures into World Models, FaceMind Raises Tens of Millions of Yuan

The AI startup FaceMind, led by 95-year-old founder Dr. Lu Hongyuan, has secured tens of millions of yuan in a Pre-A Series funding round led by StarLink Capital, with existing investor 360 Capital significantly over-subscribing. Originally focused on on-device multimodal models, the company has pivoted to developing foundational world models, which aim to predict environmental changes for applications like GUI agents and embodied AI (e.g., robotics). Dr. Lu's team gained recognition for research on low-frequency word processing and the "Adam's Law" principle, work later acknowledged by Anthropic. FaceMind's proprietary system emphasizes parameter-efficient, loop-iterative architecture for long-horizon prediction. An early product, "Diedie Club," serves as a testing ground for GUI understanding. Investors highlight the team's research depth, rapid execution, and Dr. Lu's focus on fundamental model architecture over mere scale. The funding will support continued R&D and multi-scenario validation of their world model technology.

marsbit37m ago

Post-95s Doctoral Graduate Ventures into World Models, FaceMind Raises Tens of Millions of Yuan

marsbit37m ago

From the White-Haired Stock God to the Billion-Dollar Fund Titan: The Smart People Shorting NVIDIA Are Getting Rich Using the Same Framework

From "white-haired stock god" to billionaire fund manager, those profiting from shorting NVIDIA share a common framework. The article analyzes the critical bottlenecks in the AI hardware supply chain, which have become key investment focal points. The core argument is that the real constraint on the AI boom isn't software or algorithms, but fundamental physical infrastructure. The piece dissects nine major bottlenecks, organized around the lifecycle of an AI accelerator circuit board. *Before the Board*: The pre-manufacturing stage faces constraints in EDA tools, new materials (like GaN, SiC, InP) replacing silicon, and the critical, non-renewable supply of helium for semiconductor fabrication. *On the Board*: The primary bottlenecks are High-Bandwidth Memory (HBM), essential for unleashing GPU power, and advanced packaging (e.g., CoWoS), required to integrate components. Both are in severe shortage. *Between Boards*: Chip-to-chip communication is hitting limits with copper, pushing photonics and optical interconnects (CPO) as the next-gen solution, with NVIDIA heavily investing in this area. *Around the Board*: Power delivery requires new materials (GaN/SiC) for efficient voltage conversion from 48V to sub-1V. High-density AI racks (120kW+) are forcing a shift from air to liquid cooling as the standard. *Beyond the Board*: The ultimate bottleneck is electricity. AI data centers consume power equivalent to mid-sized cities, and grid expansion lags far behind demand, causing project delays and a scramble for power contracts. Prominent investors like Leopold and "white-haired stock god" are heavily betting on these infrastructure bottlenecks. Leopold's fund, for instance, holds no NVIDIA stock but uses massive put options to short the semiconductor sector while going long on power and physical infrastructure. His thesis is that while chip competition may eventually erode margins, the scarcity of foundational elements like electricity is more persistent. The framework's validity is tied to the supply-demand gap. Major new capacity in HBM and photonics is scheduled for 2027-2028, but demand continues to outpace it. Experts like Intel's CEO suggest no relief before 2028. However, the article warns of a potential reversal around 2028-2029 if AI capex slows and new capacity floods the market, turning scarcity into oversupply. Until then, the imbalance persists.

链捕手57m ago

From the White-Haired Stock God to the Billion-Dollar Fund Titan: The Smart People Shorting NVIDIA Are Getting Rich Using the Same Framework

链捕手57m ago

28,000-Star Hit Creator Unexpectedly Fired by Google, Silicon Valley Big Shots Quickly Vie for the Talent

A nearly 7-year Google veteran, Justin Poehnelt, was fired shortly after his open-source project 'gws' (a Google Workspace CLI built in Rust) went viral, amassing over 28,000 GitHub stars. The tool, designed for both humans and AI agents, allowed terminal access to all major Workspace services like Gmail and Drive by dynamically generating commands from Google's own APIs. The dismissal came just two days after Google announced its "official" Workspace CLI at its Cloud Next 2026 conference, leading to widespread criticism that the company appropriated his work. Poehnelt believes the real reason was internal fear that his project demonstrated how AI agents could fundamentally disrupt and simplify interaction with Google's core Workspace products, potentially threatening its established business model. Following his public disclosure of the events, which garnered millions of views, tech leaders like OpenClaw's Peter Steinberger and CEOs from OpenRouter and Vercel swiftly offered him jobs, highlighting the perceived misstep by Google in letting a top-performing innovator go.

marsbit2h ago

28,000-Star Hit Creator Unexpectedly Fired by Google, Silicon Valley Big Shots Quickly Vie for the Talent