直面1亿美元罚款,MicroStrategy会抛13万枚BTC吗?

Odaily星球日报Опубліковано о 2022-09-02Востаннє оновлено о 2022-09-05

Анотація

若此次诉讼终获成功,MicroStrategy 或将受到冲击。而现金储备匮乏的 MicroStrategy,又将如何应对法币不足的危机,如何处理自己的巨额比特币持仓?

若此次诉讼终获成功,MicroStrategy 或将受到冲击。而现金储备匮乏的 MicroStrategy,又将如何应对法币不足的危机,如何处理自己的巨额比特币持仓?未来是否存在巨额比特币抛售、冲击市场的风险?

北京时间 9 月 1 日凌晨,华盛顿特区首席检察官 Karl Racine 正在起诉 MicroStrategy 公司及其联合 创始人 、前 CEO Michael Saylor 涉嫌逃税。受此消息影响,MicroStrategy 股价今日持续受挫。

对于加密世界来说,MicroStrategy 是一个独特的存在——永远的多头。根据 Bitcoin Treasuries 统计,目前 MicroStrategy 持有超 12.9 万枚比特币,在机构持仓数量中仅次于 Grayscale、block one、MTGOX。该公司前 CEO Michael Saylor ,即诉讼案的起诉对象,正是其买入比特币行为的主要推动者,在牛市是也被视为推动价格上涨的有力旗手。

若此次诉讼终获成功,MicroStrategy 或将受到冲击。而现金储备匮乏的 MicroStrategy,又将如何应对法币不足的危机,如何处理自己的巨额比特币持仓?未来是否存在巨额比特币抛售、冲击市场的风险?

高管逃税风波

昨日,首席检察官Karl Racine公开表示。 “Saylor(MicroStrategy CEO)已经在华盛顿生活了十多年,但从未缴纳过任何所得税。我们想提醒大家注意:如果你在享受到生活在我们这座伟大城市的所有好处的同时拒绝缴纳税款,我们将追究你的责任。”

而且他还不忘补充Saylor和加密世界的关系,“这位首席执行官在过去几年里成为比特币和区块链技术最公开的支持者之一,他发起了一场活动来宣传公司持有比特币的好处。”

根据检察官的指控,MicroStrategy 密谋帮助 Saylor 逃避大约2500万美元的税款。MicroStrategy 公司实际知晓 Saylor 的相关情况,但并未准确向税务当局报告,而是选择与Saylor合作,为他逃税提供便利。

检察官称 Saylor 自2014年起,就未曾履行足够的纳税义务。通过本次诉讼,检察官试图从 Saylor 和 MicroStrategy 那里收回未缴税款和罚款,总额将超过 1 亿美元。

失血的MicroStrateg

尽管起诉才拉开序幕,最终结果还要经历漫长的过程。但对 MicroStrategy 面临危机已成事实,毕竟 MicroStrategy 的现金流已经濒临枯竭了。

对于一家斥资近 40 亿美元投资的公司来说,1 亿美元似乎不算多,但税务部门是不支持加密支付的。MicroStrategy 今年 Q2 财报显示,截至 2022 年 6 月 30 日,公司的现金和现金等价物仅余为 6940 万美元。且公司经营仍在持续亏损。

本季度,MicroStrategy 的运营亏损为 9.181 亿美元,而较 2021 年同比扩大 121%。净亏损也持续扩大至 10.62 亿美元,而在 2021 年 Q2 仅为 2.993 亿美元。

数据显示,MicroStrategy 购买这些比特币总花费约 39.65 亿美元购买比特币,平均成本价为 30,700 美元,而目前却产生了巨大亏损。这也是 MicroStrategy 财报中亏损的主要来源。

钻石手还能HODL吗?

在投资者的印象中,MicroStrategy 是比特币强力的钻石手、吹鼓手、HODLer。在牛市中,这一策略尚可维持,如今持续失血的 MicroStrategy 还能 HODL 多久?

今年 6 月,MicroStrategy 曾首次转移比特币,将 2089.99 枚转移到一个新钱包。这也一度引发市场猜测,钻石手终于要卖出自己的比特币。但后续并无进一步进展公布。

对于 MicroStrategy,除了日常经营的现金流,其贷款利息也需持续支付法币。在购买庞大的比特币储备中,仅不足一半的资金来自 MicroStrategy 自身资金储备,其余大部分均来自贷款购买。

今年 3 月时,MicroStrategy 从加密银行 Silvergate 得到利率约为 4% 的 2.05 亿美元贷款,其中大部分以比特币为抵押。

借贷之时,MicroStrategy 将 LTV 维持在 200%,根据当时价格计算,价格低于 21000 美元时 MicroStrategy 将被要求追加保证金。而目前比特币早已多次跌破这一数值。若比特币继续下跌,MicroStrategy 可能还将面临更多的追加追加保证金要求。

MicroStrategy 还发行了可转换债券总计 17.5 亿美元,利率约为 0.75%。此外,还有高级担保贷款 5 亿美元,利率为 6.1%。

通过上述债务估算,MicroStrategy 从 2022 年起每年须支付利息约 3500 万美元。

过去两年,MicroStrategy 每季度的净利在剔除投资减值损失后基本维持在 1000 万美元左右。也就是说,MicroStrategy 软件业务的盈利,每年刚好大致可覆盖贷款利息。

总而言之,目前 MicroStrategy 的经营处于一个微弱的平衡之中,若 MicroStrategy 被处以巨额罚款,MicroStrategy 仅有 6940 万现金储备可供动用。届时恐怕只有卖币才交得起罚款了。

目前,税务机构对 MicroStrategy 的诉讼仍刚刚拉开序幕,MicroStrategy 这个著名的钻石手,这次还能 HODL 住吗?

Пов'язані матеріали

Where Is the AI Infrastructure Industry Chain Stuck?

The AI infrastructure (AI Infra) industry chain is facing unprecedented systemic bottlenecks, despite the rapid emergence of applications like DeepSeek and Seedance 2.0. The surge in global computing demand has exposed critical constraints across multiple layers of the supply chain—from core manufacturing equipment and data center cabling to specialty materials and cleanroom facilities. Key challenges include four major "walls": - **Memory Wall**: High-bandwidth memory (HBM) and DRAM face structural shortages as AI inference demand outpaces training, with new capacity not expected until 2027. - **Bandwidth Wall**: Data transfer speeds lag behind computing power, causing multi-level bottlenecks in-chip, between chips, and across data centers. - **Compute Wall**: Advanced chip manufacturing, reliant on EUV lithography and monopolized by ASML, remains the fundamental constraint, with supply chain fragility affecting production. - **Power Wall**: While energy demand from data centers is rising, power supply is a solvable near-term challenge through diversified energy infrastructure. Expansion is further hindered by shortages in testing equipment, IC substrates (critical for GPUs and seeing price hikes over 30%), specialty materials like low-CTE glass fiber, and high-end cleanroom facilities. Connection technologies are evolving, with copper cables resurging for short-range links due to cost and latency advantages, while optical solutions dominate long-range scenarios. Innovations like hollow-core fiber and advanced PCB technologies (e.g., glass substrates, mSAP) are emerging to meet bandwidth needs. In summary, AI Infra bottlenecks are multidimensional, spanning compute, memory, bandwidth, power, and supply chain logistics. Advanced chip manufacturing remains the core constraint, while substrate, material, and equipment shortages present immediate challenges. The industry is moving toward hybrid copper-optical solutions and accelerated domestic supply chain development.

marsbit40 хв тому

Where Is the AI Infrastructure Industry Chain Stuck?

marsbit40 хв тому

Autonomy or Compatibility: The Choice Facing China's AI Ecosystem Behind the Delay of DeepSeek V4

DeepSeek V4's repeated delay in early 2026 has sparked global discussions on "de-CUDA-ization" in AI. The highly anticipated trillion-parameter open-source model is undergoing deep adaptation to Huawei’s Ascend chips using the CANN framework, representing China’s first systematic attempt to run a core AI model outside the CUDA ecosystem. This shift, however, comes with significant engineering challenges. While the model uses a MoE architecture to reduce computational load, it places extreme demands on memory bandwidth, chip interconnects, and system scheduling—areas where NVIDIA’s mature CUDA ecosystem currently excels. Migrating to Ascend introduces complexities in hardware topology, communication latency, and software optimization due to CANN’s relative immaturity compared to CUDA. The move highlights a broader strategic dilemma: short-term compatibility with CUDA offers practical benefits and faster adoption, as seen in CANN’s efforts to emulate CUDA interfaces. Yet, long-term over-reliance on compatibility risks inheriting CUDA’s limitations and stifling native innovation. If global AI shifts away from transformer-based architectures, strict compatibility could lead to technological obsolescence. Despite these challenges, DeepSeek V4’s eventual release could demonstrate the viability of a full domestic AI stack and accelerate CANN’s ecosystem growth. However, true technological independence will require building an original software-hardware paradigm beyond compatibility—a critical task for China’s AI ambitions in the next 3-5 years.

marsbit58 хв тому

Autonomy or Compatibility: The Choice Facing China's AI Ecosystem Behind the Delay of DeepSeek V4

marsbit58 хв тому

Торгівля

Спот
Ф'ючерси
活动图片